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1. Yan Pei, “The Old Street”, Sunshine in Time, Chinese Campus Literature Series, Writers Publishing House Press, Vol.2, pp.259-261, ISBN: 7-5063-2123-8, (2001) (in Chinese).
2. Yan Pei, “Chapter 15: interactive chaotic evolution”, Swarm Intelligence: Innovation, New Algorithms and Methods, The Institution of Engineering and Technology Press, pp.417-443, ISBN:978-1-78561-313-5, e-ISBN: 9781785616303 (2018).
Book DOI: https://doi.org/10.1049/PBCE119G
Chapter DOI: https://doi.org/10.1049/PBCE119G ch15
3. Yan Pei, “Chapter 4: Trends on fitness landscape analysis in evolutionary computation and meta-heuristics”, Frontier applications of nature inspired computation in Springer Tracts in Nature-Inspired Computing (STNIC), pp.78-99, ISBN: 978-1-78561-313-5, e-ISBN: 978-981-15-2133-1 (2020).
Book DOI: https://doi.org/10.1007/978-981-15-2133-1
Chapter DOI: https://doi.org/10.1007/978-981-15-2133-1 4
4. Yang, Chao-Tung, Yan Pei, Chang, Jia-Wei (Eds.) “Innovative Computing: IC 2020 (Lecture Notes in Electrical Engineering (675)”, ISBN 978-981-15-5958-7 (2020).
Book DOI: https://doi.org/10.1007/978-981-15-5959-4
5. Jason C. Hung, Jia-Wei Chang, Yan Pei and Wei-Chen Wu (Eds.), “Innovative Computing: IC 2021 (Lecture Notes in Electrical Engineering, 791)”, ISBN 978-981-16-4257-9 (2021).
Book DOI: https://doi.org/10.1007/978-981-16-4258-6
6. Yan Pei, Jia-Wei Chang and Jason C. Hung (Eds.), “Innovative Computing: IC 2022”, ISBN 978-981-16-4257-9 (2022). ISBN: 978-981-19-4131-3
Book DOI: https://doi.org/10.1007/978-981-19-4132-0
https://link.springer.com/book/9789811941344
https://link.springer.com/book/10.1007/978-981-19-4132-0
（●: corresponding author）
1. Guang-ming Yang, Yan Pei and Aoshuang Dong, “Application Research on Reinforcement Learning Algorithm in Vehicle Navigation System”, Journal of Chinese Computer Systems, vol.29 Supplement, pp.280-283 (2008) (in Chinese).
2. Yan Pei● and Hideyuki Takagi, “Triple and Quadruple Comparison-Based Interactive Differential Evolution and Differential Evolution”, Transaction of the Japanese Society for Evolutionary Computation, vol.3, no.2, pp.98-108 (2012) (in Japanese).
https://doi.org/10.11394/tjpnsec.3.98
3. Yan Pei● and Hideyuki Takagi, “Accelerating IEC and EC Searches with Elite Obtained by Dimensionality Reduction in Regression Spaces”, Evolutionary Intelligence, vol.6, no.1, pp.27- 40 (2013).
https://doi.org/10.1007/s12065-013-0088-9
4. Yan Pei●, “Chaotic Evolution: Fusion of Chaotic Ergodicity and Evolutionary Iteration for Optimization”, Natural Computing, vol.13, no.1, pp.79-96 (2014).
https://doi.org/10.1007/s11047-013-9409-2
5. Yan Pei●, Qiangfu Zhao, and Yong Liu, “Kernel Method Based Human Model for Enhancing Interactive Evolutionary Optimization”, The Scientific World Journal, vol.2015, Article ID.185860, 12pages (2015).
https://doi.org/10.1155/2015/185860
6. Yan Pei●, “From Determinism and Probability To Chaos: Chaotic Evolution Towards Philosophy and Methodology Of Chaotic Optimization”, The Scientific World Journal, vol.2015, Article ID.704587, 14pages (2015).
https://doi.org/10.1155/2015/704587
7. Yuya Kaneda, Yan Pei, Qiangfu Zhao, Yong Liu, “Improving the Performance of the DBM Algorithm via Outlier Detection”, Journal of Information Processing, vol.23, no.4, pp.497-504 (2015).
https://doi.org/10.2197/ipsjjip.23.497
8. Yan Pei●, Shaoqiu Zheng, Ying Tan and Hideyuki Takagi, “Effectiveness of Approximation Strategy in Surrogate-assisted Fireworks Algorithm”, International Journal of Machine Learning and Cybernetics, vol.6, no.5, pp.795-810 (2015).
https://doi.org/10.1007/s13042-015-0388-8
9. Yan Pei●, “Algorithmic Mechanism Design of Evolutionary Computation”, Computational Intelligence and Neuroscience, vol.2015, Article ID 591954, 17pages (2015).
https://doi.org/10.1155/2015/591954
10. Shih-Hao Chang, Yi-Cheng Chen, Yan Pei, Chih-Ning Lii, “A Decision Tree Based Type-2 Diabetes Mellitus Lifestyle Self-Management System”, International Journal of Web and Grid Services, vol.12, no.3, pp.240-256 (2016).
https://doi.org/10.1504/IJWGS.2016.079160
11. Yan Pei● and Hideyuki Takagi, “Local Fitness Landscape from Paired Comparison-Based Memetic Search in Interactive Differential Evolution and Differential Evolution”, International Journal of Ad Hoc and Ubiquitous Computing, vol. 25, Nos. 1/2, pp.17–30 (2017).
https://doi.org/10.1504/IJAHUC.2017.10001946
12. Yan Pei●, “Principal Component Selection Using Interactive Evolutionary Computation”, Journal of Supercomputing, vol.73, no.7, pp.3002-3020 (2017).
https://doi.org/10.1007/s11227-016-1829-1
13. Yan Pei● and Hideyuki Takagi, “Research Progress Survey on Interactive Evolutionary Computation”, Journal of Ambient Intelligence and Humanized Computing (2018).
https://doi.org/10.1007/s12652-018-0861-9
14. Yan Pei●, Jun Yu, and Hideyuki Takagi, “Search Acceleration of Evolutionary Multi-objective Optimization Using an Estimated Convergence Point”, Mathematics, vol.7, no.2, pp.1-18 (2019).
https://doi.org/10.3390/math7020129
15. Honglin Zhu, Huiyan Jiang, Siqi Li, Haoming Li and Yan Pei, “A Novel Multi-space Image Reconstruction Method for Pathological Image Classification based on Structural Information”, BioMed Research International, volume 2019, Article ID 3530903, 9pages (2019).
https://doi.org/10.1155/2019/3530903
16. Jun Yu, Yuhao Li, Yan Pei, and Hideyuki Takagi, “Accelerating Evolutionary Computation Using a Convergence Point Estimated by Weighted Moving Vectors”, Complex & Intelligent Systems, vol.6, pp.55–65 (2020).
https://doi.org/10.1007/s40747-019-0111-6
17. Qing Liu, Rong-Jun Tang, Hai-Peng Ren, and Yan Pei, “Optimizing Multicast Routing Tree on Application Layer via an Encoding-Free Non-dominated Sorting Genetic Algorithm”, Applied Intelligence, vol.2020, no.50, pp.759-777 (2019).
https://doi.org/10.1007/s10489-019-01547-9
18. Azhar Imran, Jianqiqang Li, Yan Pei, Ji-Jiang Yang, and Qing Wang, “Comparative Analysis of Vessel Segmentation Techniques in Retinal Images”, IEEE Access vol.7: 114862-114887 (2019).
https://doi.org/10.1109/ACCESS.2019.2935912
19. Faheem Akhtar, Jianqiang Li, Yan Pei, Azhar Imran, Asif Rajput, Muhammad Azeem, and Qing Wang, “Diagnosis and prediction of large-for-gestational-age fetus using stacked generalization method”, Applied Sciences, vol.9, no.20, 4317 (2019).
https://doi.org/10.3390/app9204317
20. Jianqiang Li, Guanghui Fu, Yueda Chen, Pengzhi Li, Bo Liu, Yan Pei●, and Hui Feng, “A Multi-label Classification Model for Full Slice Brain Computerised Tomography Image”, BMC Bioinformatics, vol.21, Article number: 200 (2020).
https://doi.org/10.1186/s12859-020-3503-0
21. Pengzhi Li, Jianqiang Li, Yueda Chen, Yan Pei●, Guanghui Fu, and Haihua Xie, “Classification and Recognition of Computed Tomography Images Using Image Reconstruction and Information Fusion Methods”, Journal of Supercomputing, vol.77, pp.2645–2666 (2021)
https://doi.org/10.1007/s11227-020-03367-y
22. Faheem Akhtar, Jianqiang Li, Yan Pei●, Azhar Imran, Asif Rajput, Muhammad Azeem and Bo Liu, “Diagnosis of large-for-gestational-age infants using a semi-supervised feature learned from expert and Data”, Multimedia Tools and Applications, vol.79, pp.34047–34077 (2020)
https://doi.org/10.1007/s11042-020-09081-4
23. Jianqiang Li, Yu Guan, Xi Xu, Yan Pei●, Jsson C Hung, and Weiliang Qiu “Association between Alcohol Consumption and Telomere Length”, International Journal of Web and Grid Services, vol.17, no.1, pp36-59, (2021)
https://doi.org/10.1504/IJWGS.2021.113686
24. Azhar Imran, Jianqiqang Li, Yan Pei, Faheem Akhtar, Ji-Jiang Yang, and Yanping Dan, “Automated Identification of Cataract Severity Using Retinal Fundus Images”, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization (TCIV), vol.8, no.6, pp 691-698, (2020)
https://doi.org/10.1080/21681163.2020.1806733
25. Tariq Mahmooda, Jianqiang Li, Yan Pei●, Faheem Akhtar, Azhar Imran and Khalil Ur Rehman, “A Brief Survey on Breast Lesions Segmentation with Deep Learning Schemes Using Multi-Image Modalities”, IEEE Access, vol.8, pp. 165779-165809 (2020)
https://doi.org/10.1109/ACCESS.2020.3021343
26. Azhar Imran, Jianqiang Li, Yan Pei, Faheem Akhtar, Tariq Mahmood and Li Zhang, “Fundus Image Based Cataract Classification Using Hybrid Convolutional and Recurrent Neural Network”, Visual Computer, vol.37, pp.2407–2417 (2021)
https://doi.org/10.1007/s00371-020-01994-3
27. Saqib Ali, Jianqiang Li, Yan Pei●, Muhammad Saqlain, Zeeshan Shaukat, Muhammad Azeem “An effective and improved CNN-ELM classifier for handwritten digits recognition and classification”, Symmetry 2020, 12(10), 1742
https://doi.org/10.3390/sym12101742
28. Jianqiang Li, Lu Liu, Jingchao Sun, Yan Pei●, Jijiang Yang, Hui Pan, Shi Chen, and Qing Wang, “Diagnosis and Knowledge Discovery of Turner Syndrome Based on Facial Images Using Machine Learning Methods”, IEEE Access (2020), vol.8, pp 214866-214881
https://doi.org/10.1109/ACCESS.2020.3038231
29. Qing Zhao, Guohong Yao, Faheem Akhtar, Jianqiang Li, and Yan Pei●, “An Automated Approach to Diagnose Turner Syndrome Using Ensemble Learning Methods”, IEEE Access, vol.8, pp165779-165809 (2020)
https://doi.org/10.1109/ACCESS.2020.3039867
30. Khalil ur Rehman, Jianqiang Li, Yan Pei●, Anaa Yasin, Saqib Ali, and Tariq Mahmood, “Computer Vision-Based Microcalcification Detection in Digital Mammogram Using Fully Connected Depth Wise Separable Convolutional Neural Network”, Sensors, 21(14):4854. (2021)
https://doi.org/10.3390/s21144854
31. Tariq Mahmood, Jianqiang Li, Yan Pei●, Faheem Akhtar, Allah Ditta, Suhail Ashfaq Butt, and Sirajuddin Qureshi, “An Intelligent Fault Detection Approach based on Reinforcement Learning System in Wireless Sensor Network”, Journal of Supercomputing, 78, pages3646–3675 (2022).
https://doi.org/10.1007/s11227-021-04001-1
32. Tariq Mahmood, Jianqiang Li, Yan Pei●, and Faheem Akhtar, “An Automated In-depth Feature Learning Algorithm for Breast Abnormality Prognosis and Robust Characterization From Mammography Images Using Deep Transfer Learning”, biology 10, no. 9: 859. 2021.
https://doi.org/10.3390/biology10090859
33. Saqib Ali, Jianqiang Li, Yan Pei●, Rooha Khurram, Khalil ur Rehman, and Abdul Basit Rasool, “State-of-the-art challenges and perspectives in multi-organ cancer diagnosis via deep learning-based methods”, Cancers, 2021, 13(21), 5546
https://doi.org/10.3390/cancers13215546
34. Tariq Mahmood, Jianqiang Li, Yan Pei●, Azhar Imran, Faheem Akhtar, and Muhammad Yaqub, “An Automatic Detection and Localization of Mammographic Microcalcifications ROI with Multi-Scale Features Using Radiomics Analysis Approach”, Cancers, 2021, 13(23), 5916
https://doi.org/10.3390/cancers13235916
35. Khalil ur Rehman, Jianqiang Li, Yan Pei●, Anaa Yasin, Saqib Ali, and Yousaf Saeed, “Architectural Distortion-Based Digital Mammograms Classification Using Depth Wise Convolutional Neural Network”, Biology 2022, vol.11, no.1, 15,
https://doi.org/10.3390/biology11010015
36. Yanan Wang, Jianqiang Li, Yan Pei●, Zerui Ma, Yanhe Jia and Yu-Chih Wei, “An adaptive high-voltage direct current detection algorithm using cognitive wavelet transform”, Information Processing and Management, Volume 59, Issue 2, March 2022, 102867
https://doi.org/10.1016/j.ipm.2022.102867
37. Tariq Mahmood，Jianqiang Li, Yan Pei●, Faheem Akhtar, Mujeeb-ur-Rehman, and Shahbaz Hassan Wasti, “Breast Lesions Classifications of Mammographic Images Using a Deep Convolutional Neural Network-Based Approach”, PLoS ONE 17(1): e0263126. 2022
https://doi.org/10.1371/journal.pone.0263126
38. Asif Rajput, Jianqiang Li, Faheem Akhtar, Zahid Hussain Khand, Jason C. Hung, Yan Pei●, and Anko Borner, “A Content Awareness Module for a Predictive Lossless Image Compression to Achieve High Throughput Data Sharing over the Network Storage”, International Journal of Distributed Sensor Networks, vol. 18, no.3. pp.1-9 2022
https://doi.org/10.1177/15501329221083168
39. Saqib Ali, Jianqiang Li, Yan Pei●, Rooha Khurram, Khalil ur Rehman, Tariq Mahmood, “A comprehensive survey on brain tumor diagnosis using deep learning and emerging hybrid techniques with multi-modal MR image", Archives of Computational Methods in Engineering. (2022).
https://doi.org/10.1007/s11831-022-09758-z
40. Khalil ur Rehman, Jianqiang Li, Yan Pei●, Anaa Yasin, A review on machine learning techniques for the assessment of image grading in breast mammogram, International Journal of Machine Learning and Cybernetics, vol.13, pp.2609–2635 (2022).
https://doi.org/10.1007/s13042-022-01546-2
41. Daqiang Dong，Guanghui Fu，Jianqiang Li，Yan Pei，Yueda Chen，An Unsupervised Domain Adaptation Brain CT Segmentation Method Across Image Modalities and Diseases, Expert Systems With Applications, Volume 207, 30 November 2022, 118016 (2022).
https://doi.org/10.1016/j.eswa.2022.118016
42. Ruiqian Wang, Guanghui Fu, Jianqiang Li, and Yan Pei, “Diagnosis after Zoom in: A Multi-label Classification Model by Imitating Doctor Reading Habits to Diagnose Brain Diseases”, Medical Physics, vol. no. pp. 2022.
https://doi.org/10.1002/mp.15871
43. Jianqiang Li, Yu Guan, Xi Xu, Zerui Ma and Yan Pei●, Linking Phenotypes and Genotypes with Matrix Factorizations, Current Pharmaceutical Biotechnology
1. Yan Pei, “Study on Efficient Search in Evolutionary Computation”, Transactions of the Japanese Society for Artificial Intelligence, vol.30, no.1, pp.214 (2015).
http://id.nii.ac.jp/1004/00001751/
2. Jason C Hung, Yan Pei, Qingguo Zhou, Francisco Isidro Massetto, Social media processing, Multimedia Tools and Applications, 80, page34035 (2021)
https://doi.org/10.1007/s11042-021-11712-3
3Gai-Ge Wang, Xiao-Zhi Gao and Yan Pei, Call for Special Issue Papers: Deep Learning Assisted Big Data Analytics for Biomedical Applications and Digital Healthcare, Big Data Volume 9, Number 6, pp.415-416, 2021
https://doi.org/10.1089/big.2021.29049.cfp
4 Gai-Ge Wang, Xiao-Zhi Gao and Yan Pei, Modelling, Representation, and Visualization of the Remote Sensing Data for Forestry Management, Photogrammetric Engineering & Remote Sensing, Volume 88, Number 3, March 2022, pp. 164-164(1)
https://www.ingentaconnect.com/contentone/asprs/pers/2022/00000088/00000003/art00010
5 Gai-Ge Wang, Xiao-Zhi Gao and Yan Pei, Call for Special Issue Papers: Deep Learning Assisted Big Data Analytics for Biomedical Applications and Digital Healthcare, Big Data Volume 10, Number 1, Feb 2022.85-86.
https://doi.org/10.1089/big.2021.29049.cfp2
6 Yan Pei, Meet the Editorial Board Member, Current Pharmaceutical Biotechnology, Volume 23, Issue 10, 2022, 09 May, 2022, 1227 - 1227
https://doi.org/10.2174/138920102310220509162856
7. Lianbo Ma, Shangce Gao, Miqing Li, Yan Pei and Shi Cheng, Editorial: Evolutionary Multi-Objective Optimization Algorithms in Microgrid Power Dispatching，Frontiers in Energy Research
https://doi.org/10.3389/fenrg.2022.1053325
(* co-/full-supervised student paper)
1. Yan Pei and Guang-ming Yang, “Application Research on Machine Learning and the Statistic Forecast Algorithm in the Traffic Information Forecast System”, 9th International Conference on Hybrid Intelligent Systems (HIS2009), Vol.2, pp.431-436, Shenyang, China (12-14, Aug., 2009). (Poster)
https://doi.org/10.1109/HIS.2009.202
2. Yan Pei and Hideyuki Takagi, “Accelerating Evolutionary Computation with Elite Obtained in Projected One-Dimensional Spaces”, 5th International Conference on Genetic and Evolutionary Computation (ICGEC2011), pp.89-92, Kinmen Taiwan / Xiamen China (29, Aug.-1, Sept., 2011). (Oral)
https://doi.org/10.1109/ICGEC.2011.30
3. Yan Pei and Hideyuki Takagi, “A Novel Traveling Salesman Problem Solution by Accelerated Evolutionary Computation with Approximated Cost Matrix in an Industrial Application”, 3rd International Conference on Soft Computing and Pattern Recognition (SoCPaR2011), pp.39-44, Dalian, China (14-16, Oct. 2011). (Oral)
https://doi.org/10.1109/SoCPaR.2011.6089092
4. Yan Pei and Hideyuki Takagi, “A Survey on Accelerating Evolutionary Computation Approaches”, 3rd International Conference on Soft Computing and Pattern Recognition (SoCPaR2011), pp.201-206, Dalian, China (14-16, Oct. 2011). (Oral)
https://doi.org/10.1109/SoCPaR.2011.6089140
5. Yan Pei and Hideyuki Takagi, “Comparative Evaluations of Evolutionary Computation with Elite Obtained in Reduced Dimensional Spaces”, 3rd International Conference on Intelligent Networking and Collaborative Systems (INCoS2011), pp.35-40, Fukuoka, Japan (30, Nov.-2, Dec. 2011). (Oral)
https://doi.org/10.1109/INCoS.2011.66
6. Yan Pei and Hideyuki Takagi, “Fourier Analysis of the Fitness Landscape for Evolutionary Search Acceleration”, 2012 IEEE Congress on Evolutionary Computation (IEEE CEC2012), pp.2934-2940, Brisbane, Australia (June 10-15, 2012). (Oral)
https://doi.org/10.1109/CEC.2012.6252924
7. Yan Pei and Hideyuki Takagi, “Comparative Study on Fitness Landscape Approximation with Fourier Transform”, 6th International Conference on Genetic and Evolutionary Computation (ICGEC2012), pp.400-403, Kitakyushu, Japan (25-28, Aug, 2012). (Best Paper Award) (Oral)
https://doi.org/10.1109/ICGEC.2012.74
8. Yan Pei, Shaoqiu Zheng, Ying Tan and Hideyuki Takagi, “An Empirical Study on Influence of Approximation Approaches to Enhancing Fireworks Algorithm”, 2012 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2012), pp.1322-1327, Seoul, Korea (Oct. 14-17, 2012). (Oral)
https://doi.org/10.1109/ICSMC.2012.6377916
9. Yan Pei and Hideyuki Takagi, “Triple and Quadruple Comparison-Based Interactive Differential Evolution and Differential Evolution”, Foundations of Genetic Algorithms Workshop XII (FOGA2013), pp.173-182, Adelaide, Australia (Jan., 16-20, 2013) (Oral)
https://doi.org/10.1145/2460239.2460255
10. Yan Pei, “A Chaotic Ergodicity Based Evolutionary Computation Algorithm”, The 2013 9th International Conference on Natural Computation (ICNC’13), pp.454-459, Shenyang, China (Jul., 23-25, 2013).
https://doi.org/10.1109/ICNC.2013.6818019
11. Yan Pei and Hideyuki Takagi, “Fitness Landscape Approximation by Adaptive Support Vector Regression with Opposition-Based Learning”, 2013 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2013), pp.1329-1334, Manchester, UK (Oct. 13-16, 2013).
https://doi.org/10.1109/SMC.2013.230
12. Yong Liu, Qiangfu Zhao and Yan Pei, “From Low Negative Correlation Learning to High Negative Correlation Learning”, 2014 International Joint Conference on Neural Networks (IJCNN2014), pp.171-174, Beijing, China (Jul. 6-11, 2014).
https://doi.org/10.1109/IJCNN.2014.6889706
13. Yong Liu, Qiangfu Zhao and Yan Pei, “Control of Correlation in Negative Correlation Learning”, 2014 10th International Conference on Natural Computation (ICNC 2014), pp.7-11, Xiamen, China (Aug. 19-21, 2014).
https://doi.org/10.1109/ICNC.2014.6975801
14. Yong Liu, Qiangfu Zhao and Yan Pei, “Ensemble Learning with Correlation-Based Penalty”, 2014 World Ubiquitous Science Congress (U-Science 2014), pp.350–353, Dalian, China (Aug. 24-27, 2014).
https://doi.org/10.1109/10.1109/DASC.2014.69
15. Yan Pei, Hideyuki Takagi, Qiangfu Zhao and Yong Liu, “A Comprehensive Analysis on Optimization Performance of Chaotic Evolution and Its Parameter Distribution”, 2014 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2014), pp.3496-3501, San Diego, USA (Oct. 5-9, 2014).
https://doi.org/10.1109/SMC.2014.6974468
16. Yuya Kaneda, Yan Pei, Qiangfu Zhao and Yong Liu, “Study on the Effect of Learning Parameters on Decision Boundary Making Algorithm”, 2014 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2014), pp.719-724, San Diego, USA (Oct. 5-9, 2014).
https://doi.org/10.1109/SMC.2014.6973992
17. Yuya Kaneda, Yan Pei, Qiangfu Zhao and Yong Liu, “Improving Performance of DBM with SVM-Based Outlier Detection”, IEEE Symposium Series on Computational Intelligence (SSCI 2014), pp.32-37, Orlando, Florida, USA (Dec., 9-12, 2014).
https://doi.org/10.1109/INDCOMP.2014.7011745
18. Yan Pei and Hideyuki Takagi, “Local Information of Fitness Landscape Obtained by Paired Comparison-Based Memetic Search for Interactive Differential Evolution”, 2015 IEEE Congress on Evolutionary Computation (IEEE CEC2015), pp.2215-2221, Sendai, Japan (May 25-28, 2015). (Oral)
https://doi.org/10.1109/CEC.2015.7257158
19. Noboru Murata, Ryuei Nishii, Hideyuki Takagi and Yan Pei, “Analytical Estimation of the Convergence Point of Populations”, 2015 IEEE Congress on Evolutionary Computation (IEEE CEC2015), pp.2619-2624, Sendai, Japan (May 25-28, 2015). (Oral)
https://doi.org/10.1109/CEC.2015.7257211
20. Yong Liu, Qiangfu Zhao, and Yan Pei, “Bounded Learning for Neural Network Ensembles”, IEEE International Conference on Information and Automation in conjunction with IEEE International Conference on Automation and Logistics pp.1216–1221, Lijiang, Yunnan, China (August 8 - 10, 2015).
https://doi.org/10.1109/ICInfA.2015.7279472
21. Yong Liu, Qiangfu Zhao, and Yan Pei, “Error Awareness by Lower and Upper Bounds in Ensemble Learning”, 11th International Conference on Natural Computation, pp.14–18, Zhangjiajie, Hunan, China, (August 15-17 2015).
https://doi.org/10.1109/ICNC.2015.7377958
22. Yan Pei, “Strategy Equilibrium of Evolutionary Computation: towards Its Algorithmic Mechanism Design”, 2015 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2015), pp.2101-2107, Hong Kong, China (Oct. 9-12, 2015).
https://doi.org/10.1109/SMC.2015.367
23. Yan Pei, “Linear Principal Component Discriminate Analysis”, 2015 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2015), pp.2108-2113, Hong Kong, China (Oct. 9-12, 2015).
https://doi.org/10.1109/SMC.2015.368
24. Yuya Kaneda, Qiangfu Zhao, Yong Liu, and Yan Pei, “Strategies for Determining Effective Step Size of the Back propagation Algorithm for On-Line Learning”, the 7th International Conference on Soft Computing and Pattern Recognition (SoCPaR2015), pp.155-169, Fukuoka, Japan (Nov. 13-15, 2015).
https://doi.org/10.1109/SOCPAR.2015.7492800
25. Jun Yu, Yan Pei and Hideyuki Takagi, “Accelerating Evolutionary Computation Using Estimated Convergence Point”, 2016 IEEE Congress on Evolutionary Computation (IEEE CEC2016), pp.1438-1444, Vancouver, Canada (July 24-29, 2016). (Oral)
https://doi.org/10.1109/CEC.2016.7743959
26. Yan Pei, “Data Compression with Linear Discriminant Analysis”, Joint 8th International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2016), pp.136-141, Sapporo, Hokkaido, Japan (Aug. 25-28, 2016).
https://doi.org/10.1109/SCIS-ISIS.2016.0040
27. Guan-Chin Chen, Qiangfu Zhao, and Yan Pei, “Face Recognition Base on Sub-space Approaches”, The 9th IEEE International Conference on Ubi-Media Computing, pp.133-138, Moscow, Russia (Aug. 15-17, 2016).
https://www.elibrary.ru/item.asp?id=27342393
28. Yan Pei, “Principal Component Selection of Machine Learning Algorithms Based on Orthogonal Transformation by Using Interactive Evolutionary Computation”, 2016 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2016), pp.308-313, Budapest, Hungary (Oct. 9-12, 2016).
https://doi.org/10.1109/SMC.2016.7844258
29. Yan Pei and Jia Hao, “Non-dominated Sorting and Crowding Distance Based Multi-objective Chaotic Evolution”, the Eighth International Conference on Swarm Intelligence (ICSI 2017), pp.15-22, Fukuoka, Japan (Jul. 27-Aug.1st, 2017).
https://doi.org/10.1007/978-3-319-61833-3 2
30. Yan Pei, “Autoencoder Using Kernel Method”, 2017 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2017), pp.322-327, Banff, Canada (Oct. 5-8, 2017).
https://doi.org/10.1109/SMC.2017.8122623
31. Yan Pei, Jing Lei, and Jianqiang Li, “Selection Issues of Kernel Function and Its Parameters of Hard Margin Support Vector Machine in a Real-world Handwriting Device”, The 7th International Conference on Frontier Computing (FC 2018) - Theory, Technologies and Applications, pp.109-117, Kuala Lumpur, Malaysia (Jul. 3-6, 2018). (Best Paper Award) (Oral)
https://doi.org/10.1007/978-981-13-3648-5 12
*32. Van Quan Dang and Yan Pei, “A Study on Feature extraction of handwriting data using kernel method-based autoencoder”, 9th IEEE International Conference on Awareness Science and Technology (iCAST 2018), Fukuoka, Japan, pp.285-290 (19-21, Sep., 2018). (in English, Oral)
https://doi.org/10.1109/ICAwST.2018.8517169
33. Yan Pei, “Kernel PLS Regression II: Kernel Partial Least Squares Regression by Projecting Both Independent and Dependent Variables into Reproducing Kernel Hilbert Space”, 2018 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2018), pp.2027-2032, Miyazaki, Japan (Oct. 7-10, 2018). (Oral)
https://doi.org/10.1109/SMC.2018.00350
34. Jun Yu, Yan Pei, and Hideyuki Takagi, “Competitive Strategies for Differential Evolution”, 2018 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2018), pp.268-273, Miyazaki, Japan (Oct. 7-10, 2018). (Oral)
https://doi.org/10.1109/SMC.2018.00056
35. Yan Pei, and Jianqiang Li, “Chaotic Evolution with Random Crossover Rate in Single Objective Optimization Problems”, 9th International Conference on Information Technology in Medicine and Education, pp.423-427, Hangzhou, Zhejiang, China. (Oct., 19-21, 2018). (Oral)
https://doi.org/10.1109/ITME.2018.00101
36. Yan Pei, “Optimization Using Evolutionary Computation”, 2019 International Conference on Frontier Computing, Special Forum on AI&Blockchain in Healthcare, pp.32 - 33, Taichung, Taiwan. (January 19-21, 2019).
http://www.dbpia.co.kr/journal/voisDetail?voisId=VOIS00380425&language=ko KR
*37. Faheem Akhtar, Jianqiang Li, Yan Pei, and Muhammad Azeem, “A Semi-Supervised Technique for LGA Prognosis”, 2019 International Conference on Frontier Computing, Special Forum on AI&Blockchain in Healthcare, pp.36 - 37, Taichung, Taiwan. (January 19-21, 2019).
http://www.dbpia.co.kr/journal/voisDetail?voisId=VOIS00380425&language=ko KR
*38. Tianshui Li and Yan Pei, “Chaotic Evolution Algorithm Using Opposition-Based Learning”, 2019 IEEE Congress on Evolutionary Computation, pp.3292-3299, Wellington, New Zealand. (June 9 - 13, 2019).
https://doi.org/10.1109/CEC.2019.8790198
https://www.youtube.com/watch?v=fWsoXgyCP0A
*39. Guohong Yao, Jianqiang Li, Yan Pei, Faheem Akhtar and Bo Liu, “An Automatic Turner Syndrome Identification System with Facial Images”, The 9th International Conference on Frontier Computing (FC2019), Theory, Technologies and Applications, pp.105-112, Kitakyushu, Japan, (July 9-12, 2019)
https://doi.org/10.1007/978-981-15-3250-4 13
*40. Xiang Gao, Jianqiang Li, Yan Pei, and Faheem Akhtar, “Turner Syndrome Prognosis with Facial Features Extraction and Selection Schemes”, The 9th International Conference on Frontier Computing (FC2019), Theory, Technologies and Applications, pp.72-78, Kitakyushu, Japan, (July 9-12, 2019)
https://doi.org/10.1007/978-981-15-3250-4 9
*41. Faheem Akhtar, Jianqiang Li, Yan Pei, Shafaq Siraj and Zeeshan Shaukat, “Macrosomia Fetus Prediction with Cluster-based Feature Selection Scheme”, The 9th International Conference on Frontier Computing (FC2019), Theory, Technologies and Applications, pp.55-62, Kitakyushu, Japan, (July 9-12, 2019)
https://doi.org/10.1007/978-981-15-3250-4 7
*42. Faheem Akhtar, Jianqiang Li, Yan Pei, Yang Xu and Asif Rajput, “Optimal Features Subset Selection for Large for Gestational Age Classification Using GridSearch Based Recursive Feature Elimination with Cross-validation Scheme”, The 9th International Conference on Frontier Computing (FC2019), Theory, Technologies and Applications, pp.63-71, Kitakyushu, Japan, (July 9-12, 2019)
https://doi.org/10.1007/978-981-15-3250-4 8
*43. Azhar Imran, Jianqiang Li, Yan Pei, Fawaz Mahiuob Mokbal, Ji-Jiang Yang and Qing Wang, “Enhanced Intelligence Using Collective Data Augmentation for CNN Based Cataract Detection”, The 9th International Conference on Frontier Computing (FC2019), Theory, Technologies and Applications, pp.148-160, Kitakyushu, Japan, (July 9-12, 2019)
https://doi.org/10.1007/978-981-15-3250-4 18
*44. Zitong Wang, and Yan Pei, “A study on multi-objective chaotic evolution algorithms using multiple chaotic systems”, The 10th International Conference on Awareness Science and Technology (iCAST 2019), pp.22-27, Morioka, Japan (Oct. 23-25, 2019). (Oral)
https://doi.org/10.1109/ICAwST.2019.8923329
https://www.youtube.com/watch?v=6SCVAzdJKis
*45. Van Quan Dang, Yan Pei, Lei Jing, and Jianqiang Li, “Optimization of kernel method-based autoencoder using chaotic evolution algorithm”, 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019), pp.3032-3039, Xiamen, China (Dec. 6-9, 2019). (Oral)
https://doi.org/10.1109/SSCI44817.2019.9002736
46. Yan Pei, “Automatic Decision Making for Parameters of Kernel Function in Kernel Method”, 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019), pp.3214-3221, Xiamen, China (Dec. 6-9, 2019). (Oral)
https://doi.org/10.1109/SSCI44817.2019.9002691
*47. Faheem Akhtar, Jianqiang Li, Yan Pei, Bo Liu, and Azeem Muhammad “Diagnosis of Large for Gestational Age Neonates with Expert-Driven Feature Selection Technique”, 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019), pp.3159-3164, Xiamen, China (Dec. 6-9, 2019). (Oral)
https://doi.org/10.1109/SSCI44817.2019.9002960
*48. Azhar Imran, Jianqiang Li, Yan Pei, Jijiang Yang, and Qing Wang “Cataract Detection and Grading based on Retinal Images Using SOM-RBF Neural Network”, 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019), pp.2639-2645, Xiamen, China (Dec. 6-9, 2019). (Oral)
https://doi.org/10.1109/SSCI44817.2019.9002864
*49. Xiaoyu Zhan, Jianqiang Li and Yan Pei, “Detection and Diagnosis of Polyp in Computed Tomographic Colonography Images”, The 3rd International Conference on Innovative Computing (IC 2020), pp.1-9, Ho Chi Minh City, Vietnam (Jan. 14-17, 2020). (Oral)
https://doi.org/10.1007/978-981-15-5959-4_1
https://www.youtube.com/watch?v=igLIytrw7E4
50. Shih-Hao Chang, Yan Pei, and Ping-Tsai Chung, “Hash Flow: An Access Control Mechanism for Software Defined Network”, The 34th International Conference on Advanced Information Networking and Applications (AINA-2020), pp.554-565, University of Campania ”Luigi Vanvitelli”, Caserta, Italy, April 15 - 17, 2020
https://doi.org/10.1007/978-3-030-44038-1_51
*51. Yunshen Xie, Jianqiang Li and Yan Pei, “Multiple Instance Learning for Detection of Polyps in Computed Tomographic Colonography Images”, The 6th The International Conference on Information and Communication Technologies for Ageing Well and e-Health, pp.236-240, Online Stream, May 3 - 5, 2020
https://doi.org/10.5220/0009352002360240
*52. Faheem Akhtar, Anum Shakeel, Jianqiang Li and Yan Pei, and Yanping Dang, “Risk Factors Selection for Predicting Thalassemia Patients using Linear Discriminant Analysis”, 2020 Prognostics and Health Management Conference (PHM 2020), pp.1-7, Besancon, France, May 4-7, 2020.
https://doi.org/10.1109/PHM-Besancon49106.2020.00008
*53. Pengzhi Li, Jianqing Li, Haihua Xie, Yan Pei, and Hui Feng, “Recognition and Diagnosis of Computed Tomography Images Using Reconstructive Techniques”, The 10th International Conference on Frontier Computing (FC2020), Theory, Technologies and Applications, pp.1-11, Singapore (July 9-12, 2020) (Best Paper Award)
https://doi.org/10.1007/978-981-16-0115-6_1
https://www.youtube.com/watch?v=tLgBpq6MQ_Y
54. Jitong Zhang, Huiyan Jiang, Liangliang Huang and Yan Pei, “CRC-Model for Word Attributes Classification in Chinese Diagnostic Report”, The 10th International Conference on Frontier Computing (FC2020), Theory, Technologies and Applications, pp.271-282, Kitakyushu, Singapore (July 9-12, 2020). (Best Paper Award) (Oral)
https://doi.org/10.1007/978-981-16-0115-6_27
*55. Hayato Shindo, and Yan Pei, “Characteristic Analysis of Auditory Perception and Aesthetics in Sound Composition Optimization Using Revised Interactive Differential Evolution”, The Genetic and Evolutionary Computation Conference (GECCO2020), pp.1554-1561, Canc´ un, Mexico, Electronic-only Conference (July 8th-12th 2020).
https://doi.org/10.1145/3377929.3398077
https://www.youtube.com/watch?v=eUx4DwjLCwc
*56. Faheem Akhtar, Jianqiang Li, Yan Pei, Azhar Imran, Gul Mohammad Shaikh and Chun Xu “Exploiting Ensemble Classification Schemes to Improve Prognosis Process for Large for Gestational Age Fetus Classification”, IEEE Computer Society Signature Conference on Computers, Software and Applications, pp.1455-1459, Madrid, Spain, all-digital conference 13-17 July, 2020.
https:// doi.org/10.1109/COMPSAC48688.2020.00-50
*57. Thi Thoa Tran, and Yan Pei “Chaotic Evolution Algorithm with Multiple Chaotic Systems”, 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), pp.814-819, September 23-26, 2020, in Chiang Mai, Thailand.
https://doi.org/10.23919/SICE.2020.9240472
https://www.youtube.com/watch?v=DxcGq-BqyTw
58. Changwei Song, Guanghui Fu, Jianqiang Li, and Yan Pei, “An Explainable Multi-Instance Multi-Label Classification Model for Full Slice Brain CT Images”, 3rd IFAC Conference on Cyber-Physical & Human-Systems, (CPHS 2020), pp. 780-785, December 3-5, 2020 in Shanghai, China.
https://doi.org/10.1016/j.ifacol.2021.05.001
59. Yan Pei, “Chaotic Evolution Algorithm with Elite Strategy in Single-objective and Multi-objective Optimization”, 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC2020), pp.579-584, Toronto, Canada October 11–14, 2020 (a virtual conference)
https://doi.org/10.1109/SMC42975.2020.9283144
https://www.youtube.com/watch?v=AvcrnGLCWMk
60. Lu Liu, Jingchao Sun, Jianqiang Li, and Yan Pei, “Automatic Classification of Turner Syndrome Based on Unsupervised Feature Learning”, 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC2020), pp.1578-1583, Toronto, Canada October 11–14, 2020 (a virtual conference)
https://doi.org/10.1109/SMC42975.2020.9283194
61. Jianqiang Li, Jingnan Wang, Chengyao Xiong, Yanan Wang and Yan Pei, “Epidemic Data Visualization Analysis of the Covid-19 Development in China”, The 4th International Conference on Innovative Computing (IC 2021), pp. 43-51, Taichung, Taiwan (Jan. 5-8, 2021). (Oral)
https://doi.org/10.1007/978-981-16-4258-6_6
*62. Yinlong Xiao, Jianqiang Li, Qing Zhao and Yan Pei, “Emotion Recognition in Conversation Using Capsule Networks and Gated Recurrent Units”, The 4th International Conference on Innovative Computing (IC 2021), pp. 59-67, Taichung, Taiwan (Jan. 5-8, 2021).
https://doi.org/10.1007/978-981-16-4258-6_8
63. Jun Yu, Zitong Wang and Yan Pei, “Cooperative Chaotic Evolution”, 2021 IEEE Congress on Evolutionary Computation, Kraków, Poland (VIRTUAL), pp.1-6, June 28 - July 1, 2021
https://doi.org/10.1109/CEC45853.2021.9504825
https://www.youtube.com/watch?v=v0VQUy7Gl_Y
*64. Fengkai Guo and Yan Pei, “Enhancing multi-objective chaotic evolution algorithm using an estimated convergence point”, 2021 IEEE International Conference on Cybernetics (CYBCONF) (VIRTUAL), pp1-6, June 8-10, 2021
https://doi.org/10.1109/CYBCONF51991.2021.9464144
https://www.youtube.com/watch?v=zIWMsMlyX50
65. Tariq Mahmood, Jianqiang Li, Yan Pei, Faheem Akhtar, Yanhe Jia and Zahid Hussain Khand, Breast Mass Detection and Classification Using Deep Convolutional Neural Networks for Radiologist Diagnosis Assistance, IEEE Computer Society Signature Conference on Computers, Software and Applications. 45th Anniversary Conference, All-Virtual, pp.1919-1924, July 12-16, 2021
https://doi.org/10.1109/COMPSAC51774.2021.00291
*66. Chengyao Xiong, Jianqiang Li, Yan Pei, Jingyao Kang, Yanhe Jia, and Caihua Ye, An Automatic Pollen Grain Detector Using Deep Learning, The 11th International Conference on Frontier Computing (FC 2021), pp 34–44, Seoul, Korea July 13 - 17, 2021
https://doi.org/10.1007/978-981-16-8052-6_4
*67. Thi Thoa Tran and Yan Pei, “A study on chaotic evolution algorithm using multiple chaotic systems with elite strategy”, 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp.649-654, Melbourne, Australia, Going Virtual, 17 - 20 October 2021
https://doi.org/10.1109/SMC52423.2021.9659108
https://www.youtube.com/watch?v=Z-2qc0AC5x0
*68. Yanan Wang, Jianqiang Li, Yan Pei, Zerui Ma, Yanhe Jia, and Yu-Chih Wei, “An adaptive high-voltage direct current detection algorithm using wavelet transform”, 2021 IEEE Symposium Series on Computational Intelligence (SSCI) (SSCI 2021) Going Virtual, pp.1-8, December 4th – 7th 2021, Orlando, Florida, USA
https://doi.org/10.1109/SSCI50451.2021.9660158
https://www.youtube.com/watch?v=hgS5riumqeQ
*69. Khalil Ur Rehman, Jianqiang Li, Yan Pei, Anaa Yasin and Saqib Ali, A deep learning-based approach for mammographic architectural distortion classification, The 5th International Conference on Innovative Computing (IC 2022), Pages 3-14 Guam/Online, Jan 2022.
https://doi.org/10.1007/978-981-19-4132-0_1
https://www.youtube.com/watch?v=UaJlFoX2qJE&list=PL_ROeJ0xB3zN5s_TTDgwO9W7rE6WqKujC&index=4
*70. Fengwei Liu, Yan Pei, Juan Li, Fujiao Ju, Jianqiang Li and Caihua Ye, Double Upsample Dilated Pyramid Network for Pollen Detection, The 5th International Conference on Innovative Computing (IC 2022), Pages 15-29, Guam/Online, Jan 2022.
https://doi.org/10.1007/978-981-19-4132-0_2
*71. Khalil Ur Rehman, Jianqiang Li, Yan Pei, Anaa Yasin, Saqib Ali and Yousaf Saeed, A feature fusion-based approach for mammographic mass classification using deep learning, The 5th International Conference on Innovative Computing (IC 2022), Pages 62-73, Guam/Online, Jan 2022.
https://doi.org/10.1007/978-981-19-4132-0_5
https://www.youtube.com/watch?v=Vka1o-GMHV4&list=PL_ROeJ0xB3zN5s_TTDgwO9W7rE6WqKujC&index=5
*72. Dawei Li, Jianqiang Li, Zhichao Zhu, Yu-Chih Wei and Yan Pei, Chinese medical named entity recognition based on multi-word segmentation, The 5th International Conference on Innovative Computing (IC 2022), Pages 74-85, Guam/Online, Jan 2022.
https://doi.org/10.1007/978-981-19-4132-0_6
https://www.youtube.com/watch?v=yvBKsLW36h0&list=PL_ROeJ0xB3zN5s_TTDgwO9W7rE6WqKujC&index=9
*73. Yang Yu, Jianqiang Li, Zhichao Zhu, Yan Pei, Zhenning Cheng and Jieqing Chen, Chinese Electronic Medical Record Retrieval Method Using Fine-Tuned RoBERTa and Hybrid Features, Pages 86-95, The 5th International Conference on Innovative Computing (IC 2022), Guam/Online, Jan 2022.
https://doi.org/10.1007/978-981-19-4132-0_7
*74. Yanan Li, Jianqiang Li, Yan Pei, and Jin Wang, A Dual-channel Attention Model for Optical Microscope Pollen Classification, the 8th International Conference on Control, Decision and Information Technologies (CODIT) (CoDIT 2022), pp.1118-1123, Istanbul, Turkey, May 17-20, 2022.
https://doi.org/10.1109/euca.CODiT22.291.8e945eb0
*75. Yuhei Yamaya and Yan Pei, "An Analysis on Effectiveness of Estimated Convergence Points for Enhancement of Multi-objective Optimization Algorithms", Genetic and Evolutionary Computation Conference (GECCO-2022), pp.371-374, Boston, USA, 9-13, July 2022.
https://doi.org/10.1145/3520304.3528968
https://www.youtube.com/watch?v=mGUDQfaKZN4
76. Zhuo Su, Bo Liu, Jianqiang Li and Yan Pei，An improved method for Chinese relationship extraction，The 12th International Conference on Frontier Computing (FC 2022). Japan July 13 - 17, 2022
https://www.youtube.com/watch?v=0S5uykR8lb0
77. Xiang Meng, Yi Ding, Yan Pei, Chaotic Evolution Using Deterministic Crowding Method for Multi-modal Optimization, 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC2022), pp807-812, Clarion Congress Hotel Prague, Czech Republic, October 9–12, 2022 (FACE-to-FACE Conference, allowing the authors of accepted papers from the countries with pandemic travel restrictions to present their contributions in a videoconference mode)
https://doi.org/10.1109/SMC53654.2022.9945158
https://www.youtube.com/watch?v=Qj0wFYBVcqw
78. Jun Yu and Yan Pei, Chaotic Evolution for Multimodal Optimization Using Local Dominance Rules, 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS) held in Ise-Shima, Mie, Japan, on November 29 - December 2, 2022
79. Saqib Ali, Jianqiang Li, Yan Pei and Khalil Ur Rehman, A multi-module 3D U-Net learning architecture for brain tumor segmentation, the Seventh International Conference on Data Mining and Big Data (DMBD'2022) to be held on November 21-24, 2022, Beijing, China,
80. Bo Liu, Jidong Zhang, Yuxiao Xu, Jianqiang Li, Yan Pei, Guanzhi Qu, A multimodal sentiment recognition method based on attention mechanism, 2022 5th Artificial Intelligence and Cloud Computing Conference (AICCC 2022), Osaka, 17-19 December, 2022
1. Yan Pei and Hideyuki Takagi, “Approximating and Analyzing Fitness Landscape for Evolutionary Search Enhancement”, Satellite Workshop on Problem, Landscape Analysis, Automated Algorithm Selection and Adaptation in Optimization at Foundations of Genetic Algorithms Workshop XII (FOGA2013), 3 pages, Adelaide, Australia (Jan., 16-20, 2013) (Oral)
https://catalog.lib.kyushu-u.ac.jp/opac_detail_md/?lang=0&amode=MD100000&bibid=1434429
2. Yan Pei, Kenichi Utano, Kusanagi Yoshihiro, Xin Zhu, Kazu Togashi, “Detection of Colorectal Polyps from CT Colonoscopy Using Support Vector Machine”, International Symposium on Biomedical Imaging (ISBI’19), pp.972, Hilton Molino Stucky, Venice, Italy (April 8 - 11, 2019). (Oral)
3. Guanghui Fu, Jianqiang Li and Yan Pei, “A Multi-label classification Model for Full Slice Brain Computerised Tomography Image”, 15th International Symposium on Bioinformatics Research and Applications (ISBRA), pp.1-6, Technical University of Catalonia, Barcelona, Spain, (June 3 - 6 2019). (Oral)
（un-refereed）(* co-/full-supervised student paper)
1. Yan Pei and Guang-ming Yang, “Algorithms Model of Optimization Path Base on Vector Hypergraph”, Proceeding of 14th Youth Conf. on Communication, pp.36-40, Dalian Polytechnical University, Dalian, China, (24-26, Jul., 2009). (in Chinese, Poster)
裴岩, 杨广明, “一种基于矢量超图的最优路径算法模型”, 第14届青年通信学术会议, pp.36-40, 大连, 中国 (24-26, Jul., 2009)
https://file.scirp.org/pdf/16-1.9.pdf
2. Yan Pei and Hideyuki Takagi, “Accelerating Evolutionary Computation with Elite Obtained by Dimensionality Reduction”, Joint meeting of 7th Evolutionary Computation Frontier (SIG-ECF) meeting and 1st Evolutionary Computation Meeting, pp.25-31, Tokyo University Hongo Campus, Tokyo, Japan (9-10, Sep., 2011). (in English and in Japanese, Poster)
裴岩, 高木英行「次元削減によって得られたエリートを用いた進化計算の高速化」第7回進化計算研究会・第7回進化計算フロンティア研究会合同研究会, pp.25-31, 東京, 日本(2011年9月）.
3. Yan Pei and Hideyuki Takagi, “Fourier Analysis of Fitness Landscape to Accelerate Evolutionary Search”, Evolutionary Computation Symposium 2011, pp.167-173, Iwanuma, Miyagi Prefecture, Japan (17-18, Dec., 2011). (in English and in Japanese, Poster)
裴岩, 高木英行, 「適応度景観のフーリエ解析による進化的探索高速化の試み」, 進化計算シンポジウム2011, pp.167-173, 岩沼, 日本(2011年12月17-18日）.
4. Yan Pei and Hideyuki Takagi, “Fourier Niching Approach for Multi-modal Optimization”, Joint meeting of 8th Evolutionary Computation Frontier (SIG-ECF) meeting and 2nd Evolutionary Computation Meeting, pp.193-199, Osaka University Toyonaka Campus, Osaka, Japan (9-10, Mar., 2012). (in English and in Japanese, Oral)
裴岩, 高木英行「多峰性最適化のためのフーリエ・ニッチ法」, 第2回進化計算学会研究会・第8回進化計算フロンティア研究会合同研究会, pp.189-195, 豊中, 日本(2012年3月9-10日).
5. Yan Pei and Hideyuki Takagi, “Triple and Quadruple Comparison-Based Interactive Differential Evolution and Differential Evolution”, 3rd Evolutionary Computation Meeting, pp.74-84, Hiroshima University Higashi-Hiroshima Campus, Hiroshima, Japan (9-10, Sep., 2012). (in English and in Japanese, Oral)
裴岩, 高木英行, 「3点および4点比較ベースの対話型差分進化と差分進化」, 第3回進化計算学会研究会, pp.74-84, 広島, 日本 (2012年9月3-4日).
6. Yan Pei and Hideyuki Takagi, “Approximating and Analyzing Fitness Landscape for Evolutionary Search Enhancement”, 14th Japan Society for Fuzzy Theory and Intelligent Informatics Kyushu Chapter Annual Conference (SOFT-Kysuhu2012), pp.21-24, Saga, Japan (Dec., 8, 2012). (in English and in Japanese, Oral) (Excellent Presentation Award)
裴岩, 高木英行, 「適応度景観の近似と解析による進化計算の探索能力の向上」, 第14回日本知能情報ファジィ学会九州支部学術講演会, pp.21-24, 佐賀, 日本 (2012年12月8日). 「優秀講演賞」
7. Yan Pei, “Chaotic Evolution: Fusion of Evolutionary Iteration Property and Chaotic Ergodicity Mechanism”, Japanese Society for Evolutionary Computation Symposium 2012, Karuizawa, Nagano, Japan, pp.256-263 (15-16, Dec., 2012). (in English, Poster)
裴岩, 「カオス進化： 進化的反復特性とカオスエルゴードメカニズムの融合」, 進化計算シンポジウム2012, 軽井沢, 日本, pp.256-263 (2012年12月15-16日).
8. Hideyuki Takagi and Yan Pei, “Proposal of a Method for Accelerating Transition from Exploration to Exploitation”, 4th Evolutionary Computation Meeting, Japan Army University, Yokosuka, Japan, pp.96-101 (18-19, Mar., 2013). (in Japanese, Poster)
高木英行, 裴岩, 「Exploration からExploitation への変化を加速する手法の提案」, 第4回進化計算学会研究会, 防衛大学校, 神奈川県横須賀市, 日本, pp.96-101 (2013年3月18-19日).
9. Yan Pei and Hideyuki Takagi, “Proposal of a method for determining search states of Markov Chain practically and its application to predict EC convergence”, Japanese Society for Evolutionary Computation Symposium 2013, Kirishima, Kagoshima, Japan, pp.124-127 (14-15, Dec., 2013). (in English, Poster)
裴岩, 高木英行, 「マルコフ連鎖の探索状態決定方法の提案と進化計算収束予測への応用」, 進化計算シンポジウム2013资料集, 鹿児島県霧島市, 日本, pp.124-127 (2013年12月14-15日).
10. Yan Pei, “Chaotic Evolution”, 6th Evolutionary Computation Meeting, pp.33-52 The University of Electro-Communications, Chofu, Tokyo, Japan (6-7, Mar., 2014). (in English, Oral)
裴岩, 「カオス進化」, 第6回進化計算学会研究会, pp.33-52 電気通信大学, 調布市, 東京都, 日本 (2014年3月7-8日).
11. Yan Pei and Hideyuki Takagi, “Local fitness landscape from paired comparison based memetic search in interactive differential evolution”, 7th Evolutionary Computation Meeting, Kinki University, Osaka, Japan, pp.5-13 (28-29, Aug., 2014). (in English, Poster)
裴岩, 高木英行, 「対比較ベースの Memetic 探索による局所 fitness 景観情報を用いた対話型差分進化」, 第７回進化計算学会研究会, 大阪府東大阪市, pp.5-13, (2014年8月28日〜29日) （in English）.
12. Yuya Kaneda, Yan Pei, Qiangfu Zhao and Yong Liu, “Improving the DBM Algorithm based on Chebyshev Theorem”, The 24th Fuzzy, Artificial Intelligence, Neural Networks and Computational Intelligence, pp.135-138, Kitami, Hokkaido, (18-19, Sep., 2014). (in Japanese)
金田祐也, 裴岩, 趙強福, 刘勇, 「チェビシェフの定理を基にした判別境界作成アルゴリズムの高性能化」, 第24回インテリジェント・システム・シンポジウム, pp.135-138, 北海道北見市, (2014年9月18日〜19日)
https://dl.ndl.go.jp/info:ndljp/pid/11134381
13. Noboru Murata, Ryuei Nishii, Hideyuki Takagi and Yan Pei, “Estimation Methods of the Convergence Point of Moving Vectors Between Generations”, Japanese Society for Evolutionary Computation Symposium 2014, Hiroshima, Japan, pp.210-215 (20-21, Dec., 2014). (in Japanese,
Poster)
村田昇, 西井龍映, 高木英行, 裴岩「世代間移動ベクトル群の収束点推定法」 2014進化計算シンポジウム, pp.210-215廿日市市 (2014年12月20-21日).
14. Yan Pei, “Establishing theoretical fundamental of algorithmic mechanism design for evolutionary computation”, Japanese Society for Evolutionary Computation Symposium 2014, Hiroshima, Japan, pp.341-350 (20-21, Dec., 2014). (in English, Poster)
裴岩, 「進化計算のためのアルゴリズミックメカニズム設計理論の構築」 2014進化計算シンポジウム, , pp.341-350 廿日市市 (2014年12月20-21日).
15. Hideyuki Takagi, Makoto Inoue, and Yan Pei, “Introduction of Acceptability to evolutionary multi-objective optimization”, 9th Evolutionary Computation Meeting, RIKEN, Kobe, Japan, pp.18-23 (7-8, Sep., 2015). (in Japanese, Poster)
高木英行, 井上誠, 裴岩, 「多目的最適化への受容度概念の導入」第9回進化計算学会研究会, pp.18-23, 神戸市(2015年9月7-8日).
16. Yan Pei, Jun Yu and Hideyuki Takagi, “Evaluation of EC Acceleration by Using Estimated Points”, Japanese Society for Evolutionary Computation Symposium 2015, Hiroshima, Japan, pp.292-297 (19-20, Dec., 2015). (in Japanese, Poster)
裴岩, 余俊, 高木英行「推定収束点を用いた進化計算高速化の評価」進化計算シンポジウム 2015, pp.292-297, 西尾 (2015年12月19-20日).
17. Makoto Inoue, Mizuki Takahashi, Yan Pei and Hideyuki Takagi, “Acceptability-based Many objective Search for Selecting Rental Apartments”, 11th Evolutionary Computation Meeting, Kobe, Japan, pp.183-189 (14-15, Sep., 2016). (in Japanese, Poster)
井上誠, 裴岩, 高木英行「受容度に基づく多数目的探索のお部屋探し」, 第11回進化計算研究会, pp.183-199, 神戸 (2016年9月14-15日）
18. Yan Pei, “Autoencoder Using Kernel Method”, The society of instrument and control engineers, Tohoku chapter, Aizuwakamatsu, Japan, pp.1-10 (25, Nov., 2016). (in English, Oral)
裴岩, 「カーネル法に基づく自己符号化器」, 計測自動制御学会 東北支部 第305回 研究集会, 会津若松, pp.1-10 (2016年11月25日(金)）.
https://www.topic.ad.jp/sice/htdocs/papers/305/305-4.pdf
*19. Yuki Yamazumi and Yan Pei, “Investigation on Crossover Rate of Chaotic Evolution”, Japanese Society for Evolutionary Computation Symposium 2016, Chiba, Japan, pp.231-235 (10-11, Dec., 2016). (in Japanese, Poster)
山住優希, 裴 岩, 「カオス進化の交叉率に関する調査」, pp.231-235, 進化計算シンポジウム2016, 長生郡一宮町, (2016年12月10-11日).
20. Makoto Inoue, Mizuki Takahashi, Yan Pei and Hideyuki Takagi, 「賃貸物件の多数属性に対するユーザの受容程度の関数を導入した住まい探し」IDRユーザフォーラム2016, ポスター番号9, 東京, (2016年11月30 日).
井上誠, 高橋瑞稀, 裴岩, 高木英行, 「賃貸物件の多数属性に対するユーザの受容程度の関数を導入した住まい探し」IDRユーザフォーラム2016, ポスター番号9, 東京, (2016年11月30 日).
https://www.nii.ac.jp/dsc/idr/userforum/poster/IDR-UF2016_P09.pdf
21. Yan Pei, “Principal Component Selection Using Interactive Evolutionary Computation”, 12th Evolutionary Computation Meeting, Fukuoka, Japan, pp.123-136 (13-14, Mar., 2017). (in English, Oral)
裴岩, 「対話型進化計算を用いた主成分の選択」, 第12回進化計算研究会, pp. 123-136, 福岡 (2017年3月14-15日）
22. Makoto Inoue, Yan Pei, and Hideyuki Takagi “Design Acceptability for Many-objective Optimization: Silent Supersonic Technology Demonstrator as a Task”, 12th Evolutionary Computation Meeting, Fukuoka, Japan, pp.81-88 (13-14, Mar., 2017). (in Japanese, Poster)
井上誠, 裴岩, 高木英行「多数目的最適化を目指した設計受容度 -- 静粛超音速研究機をタスクとして --」第12 回進化計算学会研究会プログラム, 福岡, pp.81-88 (2017年3月13-14日）
*23. Kodai Sasaki and Yan Pei, “Study on three differential vectors-based differential evolution algorithm”, Japanese Society for Evolutionary Computation Symposium 2017, Hokkaido, Japan, pp.310-3175 (9-10, Dec., 2017). (in Japanese, Poster)
佐々木航大, 裴岩, 「3つの差分ベクターに基づく差分進化算法に関する研究」, pp.310-317, 進化計算シンポジウム2017, 北海道茅部郡森町, (2017年12月8-9日).
24. Yan Pei and Hideyuki Takagi, “Acceleration search of Multi-objective optimization using an estimated point”, Japanese Society for Evolutionary Computation Symposium 2017, Hokkaido, Japan, pp.411-417 (9-10, Dec., 2017). (in Japanese, Poster)
裴岩, 高木英行, 「推定収束点を用いた多目的最適化の高速化」, pp. 411-417, 進化計算シンポジウム2017, 北海道茅部郡森町, (2017年12月8-9日).
25. Yan Pei, “Interactive Chaotic Evolution”, SICE Life Engineering Symposium 2018, Aizu-wakamatsu, Japan, pp.69-73 (10-12, Sep., 2018). (in English, Oral)
裴岩, 「対話型カオス進化」, pp. 69-73, SICEライフエンジニアリング部門シンポジウム（第33回生体・生理工学シンポジウム）, 会津若松, (2018年9月10-12日).
*26. Van Quan Dang and Yan Pei, “Feature extraction of handwriting data using kernel methodbased autoencoder”, SICE Life Engineering Symposium 2018, Aizu-wakamatsu, Japan, pp.74-81 (10-12, Sep., 2018). (in English, Oral)
Van Quan Dang, 裴岩, 「カーネル法に基づく自己符号化器による手書きデータの特徴抽出, pp. 74-81, SICEライフエンジニアリング部門シンポジウム（第33回生体・生理工学シンポジウム）, 会津若松, (2018年9月10-12日).
*27. Tianshu Li and Yan Pei, “Triple and Quadruple Comparison-Based Chaotic Evolution Algorithms”, Japanese Society for Evolutionary Computation Symposium 2018, Fukuoka, Japan, pp.107-114 (8-9, Dec., 2018). (in English, Poster)
李天水, 裴岩, 「Triple and Quadruple Comparison-Based Chaotic Evolution Algorithm」, pp.107-114, 進化計算シンポジウム2018, 福岡県福岡市休暇村志賀島, (2018年12月8-9日).
*28. Yoshiki Namikawa and Yan Pei, “Mixed base vectors-based differential evolution algorithm”, Japanese Society for Evolutionary Computation Symposium 2018, Fukuoka, Japan, pp.115-120 (8-9, Dec., 2018). (in Japanese, Poster)
並河芳樹, 裴岩, 「混合ベースべクターを用いた差分進化算法」, pp.115-120, 進化計算シンポジウム2018, 福岡県福岡市休暇村志賀島, (2018年12月8-9日).
*29. Shoto Abe and Yan Pei, “Outcome optimization of mixed strategy Nash equilibrium game using differential evolution”, Japanese Society for Evolutionary Computation Symposium 2018, Fukuoka, Japan, pp.223-230 (8-9, Dec., 2018). (in Japanese, Poster)
阿部翔斗, 裴岩, 「差分進化による混合戦略ゲームにおけるナッシュ均衡の得利の最適化」, pp.223-230, 進化計算シンポジウム2018, 福岡県福岡市休暇村志賀島, (2018年12月8-9日).
*30. Zitong Wang and Yan Pei, “A study on multi-objective chaotic evolution algorithms using multiple chaotic systems”, The society of instrument and control engineers, Tohoku chapter, Aizuwakamatsu, Japan, pp.1-14 (15, Nov., 2019). (in English, Oral)
王梓铜, 裴岩, 「多重カオスシステムを用いた多目的カオス進化アルゴリズムに関する研究」, 計測自動制御学会 東北支部 第326回 研究集会, 会津若松, pp.1-14 (2019年11月15日(金)）.
*31. Tran Thi Thoa and Yan Pei, “Chaotic Evolution Using Multiple Chaotic System”, The society of instrument and control engineers, Tohoku chapter, Aizuwakamatsu, Japan, pp.1-14 (15, Nov., 2019). (in English, Oral)
Tran Thi Thoa, 裴岩, 「Chaotic Evolution Using Multiple Chaotic System」, 計測自動制御学会 東北支部 第326回 研究集会, 会津若松, pp.1-14 (2019年11月15日(金)）.
*32. Hayato Shindo and Yan Pei, “Composition of Sound with User’s Subjective Evaluation Using Interactive Differential Evolution”, 17th Evolutionary Computation Meeting, Tokyo, Japan, pp.1-8 (28-29, Feb., 2020). (in Japanese, Poster, canceled due to COVID-19)
新藤勇人, 裴岩, 「対話型差分進化によるユーザーの主観評価を反映させた音の創作」第17 回進化計算学会研究会プログラム, 東京, pp.1-8 (2020年2月28-29日）
*33. Hayato Shindo and Yan Pei, “Composition of Sound with User’s Subjective Evaluation Using Interactive Differential Evolution”, 18th Evolutionary Computation Meeting, Tokyo, Japan, pp.1-8 (15-16, Sep., 2020). (in Japanese, Oral, online)
新藤勇人, 裴岩, 「対話型差分進化によるユーザーの主観評価を反映させた音の創作」第18 回進化計算学会研究会プログラム, オンライン, pp.1-8 (2020年9月15-16日）
https://www.youtube.com/watch?v=-TOfJQLeyLc
*34. Fengkai Guo and Yan Pei, “Acceleration of multi-objective chaotic evolution algorithm using an estimated convergence point”, 18th Evolutionary Computation Meeting, Tokyo, Japan, pp.31-40 (15-16, Sep., 2020). (in Japanese, Oral, online)
郭豊愷, 裴岩, 「推定収束点を用いた多目的カオス進化算法の高速化」, 第18 回進化計算学会研究会プログラム, オンライン, pp.31-40 (2020年9月15-16日）
https://www.youtube.com/watch?v=19MJfPCEeDA
*35. Yuhei Yamaya, Fengkai Guo and Yan Pei, “acceleration search of multi-objective chaotic evolution using estimated convergence points in each objective function”, Japanese Society for Evolutionary Computation Symposium 2020, online, pp.160-167 (8-9, Dec., 2020). (in Japanese)
山谷侑平, 郭豊愷, 裴岩, 「各目的関数において推定された収束点を用いた多目的カオス進化算法の高度化」, 進化計算シンポジウム2020, オンライン, pp.160-167 (2020年12月19-20日).
https://www.youtube.com/watch?v=8C8Z9Y2ZGg8
*36. Hayato Shindo and Yan Pei, “Sound Synthesis and Timbre Optimization Using Interactive Evolutionary Computation”, 19th Evolutionary Computation Meeting, Tokyo, Japan, pp.41-54 (3-4, Mar., 2021). (in Japanese, Oral, online)
新藤勇人, 裴岩, 「対話型進化計算を用いた音の合成と音色の最適化問題」第19 回進化計算学会研究会プログラム, オンライン, pp.41-54 (2021年3月3-4日）
https://www.youtube.com/watch?v=erURVn5N5CQ
*37. Yuhei Yamaya, and Yan Pei, “Search Enhancement of Multi-objective Optimization Algorithms Using Estimated Convergence Points and Evaluation of Its Effectiveness”, Japanese Society for Evolutionary Computation Symposium 2020, online, pp.269-276 (25-26, Dec., 2020). (in Japanese)
山谷侑平, 裴岩, 「推定収束点による多目的最適化アルゴリズムの高速化とその有効性評価」, 進化計算シンポジウム2021, オンライン, pp.269-276 (2020年12月25-26日).
https://www.youtube.com/watch?v=0QRp-KWH0Kg
*38. Yi Ding and Yan Pei, “Chaotic Evolution Algorithm in Combinatorial Optimization for Solving Travel Salesman Problem”, Japanese Society for Evolutionary Computation Symposium 2021, online, pp. 130- 140 (25-26, Dec., 2021). (in English)
丁 一, 裴岩, 「組み合わせ最適化のためのカオス進化算法を用いた巡回セールスマン問題の解法」, 進化計算シンポジウム2021, オンライン, pp.130- 140 (2021年12月25-26日).
https://www.youtube.com/watch?v=r67ah53P4EA
*39. Yanan Wang and Yan Pei, A comprehensive analysis of sound composition optimization using interactive evolutionary computation, 21th Evolutionary Computation Meeting, Online, pp.15-23 (17-18, Mar., 2022). (in English, Oral, online)
王延安, 裴岩，対話型進化計算を用いた音声合成の最適化の分析, 第21回進化計算学会研究会プログラム, オンライン, pp.15-23 (2022年3月17-18日）
https://www.youtube.com/watch?v=jncjgpg-mlA
*40. Pu Cao and Yan Pei, chaotic method-based symbolic regression in genetic programming, 22th Evolutionary Computation Meeting, Online, pp. 57-63 (7-8, Sep., 2022). (in English, Oral, online)
曹朴, 裴岩，遺伝的プログラミングを用いたカオス手法ベースの関数同定，第22回進化計算学会研究会, 東京理科大学神楽坂キャンパス+オンライン，pp. 57-63 (2022年9月7-8日）
https://www.youtube.com/watch?v=Z8YIPZ5Q4fE
*41. Zitong Wang and Yan Pei, A study on multi-objective chaotic evolution algorithms
using multiple chaotic systems, 22th Evolutionary Computation Meeting, Online, pp. 1-8 (7-8, Sep., 2022). (in English, Oral, online)
王梓铜, 裴岩，複数のカオスシステムを用いた多目的カオス進化アルゴリズムに関する研究，第22回進化計算学会研究会, 東京理科大学神楽坂キャンパス+オンライン，pp.1-8 (2022年9月7-8日）
*42. Xiang Meng and Yan Pei, Chaotic Evolution Using Deterministic Crowding Method for Multi-modal Optimization, 22th Evolutionary Computation Meeting, Online, pp.77-84 (7-8, Sep., 2022). (in English, Oral, online)
孟響, 裴岩，カオス進化算法を用いた多峰性最適化問題のニッチング方法に関する研究，第22回進化計算学会研究会, 東京理科大学神楽坂キャンパス+オンライン，pp.77-84 (2022年9月7-8日）
*43. Hiroki Yaginuma and Yan Pei, Optimal Strategy Generation of Werewolf Game using Coevolutionary Algorithm, 22th Evolutionary Computation Meeting, Online, pp.54-56 (7-8, Sep., 2022). (in Japanese, Oral, online)
柳沼広輝, 裴岩，共進化計算を用いた人狼ゲームの最適化戦略の生成，第22回進化計算学会研究会, 東京理科大学神楽坂キャンパス+オンライン，pp.54-56 (2022年9月7-8日）
https://www.youtube.com/watch?v=iklzaQXL5dU
*44. Yanan Wang and Yan Pei, Title: A survey of Interactive evolutionary computation in human senses., Japanese Society for Evolutionary Computation Symposium 2022， Hokkaido， Sapporo, pp.193- 200 (17-18, Dec, 2022). (in English, Oral)
王延安, 裴岩，対話型進化計算を用いた人間の五感の研究に関する調査, 進化計算シンポジウム2022 2022年12月17日(土)-18日(日) ，pp.193- 200 北海道札幌
https://www.youtube.com/watch?v=lwFdrsQXeYg
*45. Lingxiao Qu and Yan Pei, “kernelized linear principal component discriminant analysis”, The society of instrument and control engineers, Tohoku chapter, pp.XX- XX, Aizuwakamatsu, Japan (23, Dec., 2022). (in English, Oral)
曲凌晓, 裴岩, 「カーネル法による線形主成分判別分析」, 計測自動制御学会東北支部第340回研究集会, pp.XX- XX ,会津若松(2022年12月23日(金)）.
1. Yan Pei, “Investigation and Implementation on the Algorithm of the Optimization Path in the Vehicle Navigation System”, Bachelor of Engineering, Northeastern University, China, 2005 (in Chinese).
裴岩, “汽车导航系统中最优路径算法的研究和实现”, 工学学士, 学士学位论文, 东北大学, 中国, 2005.
2. Yan Pei, “Vehicle Navigation Systems, Optimization Algorithm, Geographic Information System”, Master of Engineering, 2008 (in Chinese)
裴岩, “机器学习理论研究及其在车载导航系统中的应用”, 工学硕士, 硕士学位论文, 东北大学, 中国, 2008.
https://cdmd.cnki.com.cn/Article/CDMD-10145-2010055868.htm
3. Yan Pei, “Study on Efficient Search in Evolutionary Computation”, A dissertation submitted in partial satisfaction of the requirements for the Doctorate of Engineering, Doctor of Engineering, Kyushu University, Fukuoka, 2013 (in English).
裴岩、進化計算の効率的探索に関する研究、博士（工学）、課程博士学位論文、九州大学、福岡, 2013
https://doi.org/10.15017/1441250
https://dl.ndl.go.jp/info:ndljp/pid/8949490
1. Yan Pei, Kun Cao, Bing Fu, Yujia Lin, Hongyuan Chen and Yao Xu, “Method and system for determining recommended passage place sequence”, China Patent (Invention), Application No. CN201110032798.4, Filed on 24 Jan., 2011. (Authorized, CN Patent number 102158799)
https://patentimages.storage.googleapis.com/66/21/39/102727fd18a81b/CN102158799B.pdf
2. 李建强, 谢海华, 句福娇, 祖宝开, 裴岩, “基于自适应特征金字塔的花粉检测方法”, CN 111429510 A, China Patent(Invention)
https://patentimages.storage.googleapis.com/8d/21/bc/81d887cd302a7e/CN111429510A.pdf
1. Best Paper Award, Sixth Int. Conf. on Genetic and Evolutionary Computation (ICGEC2012), Kitakyushu, Japan (25-28, Aug, 2012).
(Awarded Paper: Yan Pei and Hideyuki Takagi, “Comparative Study on Fitness Landscape Approximation with Fourier Transform”)
2. Excellent Presentation Award, 14th Japan Society for Fuzzy Theory and Intelligent Informatics Kyushu Chapter Annual Conference (SOFT-Kysuhu2012), Saga, Japan (Dec., 8, 2012).
(Awarded Paper: Yan Pei and Hideyuki Takagi, “Approximating and Analyzing Fitness Landscape for Evolutionary Search Enhancement”)
3. Best Paper Award, The 8th International Conference on Frontier Computing (FC 2018) - Theory, Technologies and Applications, Kuala Lumpur, Malaysia (Jul. 3-6, 2018).
(Awarded Paper: Yan Pei, Jing Lei, and Jianqiang Li, “Selection Issues of Kernel Function and Its Parameters of Hard Margin Support Vector Machine in a Real-world Handwriting Device”)
4. Best Paper Award, The 9th International Conference on Frontier Computing (FC2019), Theory, Technologies and Applications, Kitakyushu, Japan, (July 9-12, 2019).
(Awarded Paper: Jitong Zhang, Huiyan Jiang, Liangliang Huang and Yan Pei, “CRC-Model for Word Attributes Classification in Chinese Diagnostic Report”)
5. Best Paper Award, The 11th International Conference on Frontier Computing (FC2020), Theory, Technologies and Applications, pp.1-11, Singapore (July 9-12, 2020)
(Awarded Paper: Pengzhi Li, Jianqiang Li, Haihua Xie, Yan Pei, Hui Feng, “Recognition and Diagnosis of Computed Tomography Images Using Reconstructive Techniques”)
6 IEEE Japan Medal, Yan Pei, awarded by IEEE Japan Council, 2021.