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ORCIDFei Han 0001
Person information
- affiliation: Jiangsu University, School of Computer Science and Communication Engineering, Zhenjiang, China
- affiliation (former): Chinese Academy of Science, Hefei Institute of Intelligent Machines, Intelligent Computation Lab, China
- affiliation (PhD 2006): University of Science and Technology of China, Department of Automation, Hefei, China
Other persons with the same name
- Fei Han — disambiguation page
- Fei Han 0002
![[0000-0002-8619-3987]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-8619-3987")
— Colorado School of Mines, Department of Electrical Engineering and Computer Science, Human-Centered Robotics Laboratory, Golden, CO, USA - Fei Han 0003 — Northeast Petroleum University, Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Daqing, China (and 2 more)
- Fei Han 0004 — US Department of Agriculture, Washington, DC, USA (and 2 more)
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2020 – today
- 2024
[j39]Zhe Liu, Fei Han, Qinghua Ling, Henry Han, Jing Jiang:
A fast interpolation-based multi-objective evolutionary algorithm for large-scale multi-objective optimization problems. Soft Comput. 28(9-10): 6475-6499 (2024)- [c39]Jing Wu, Yanqiong Ren, Fei Han, Xiang Bao:
Prediction of Bladder Cancer Prognosis by Deep Cox Proportional Hazards Model Based on Adversarial Autoencoder. ICIC (LNBI 1) 2024: 123-134 - 2023
- [j38]Fei Han, Tianyi Wang, Qinghua Ling:
An improved feature selection method based on angle-guided multi-objective PSO and feature-label mutual information. Appl. Intell. 53(3): 3545-3562 (2023) - [j37]Jeremiah Osei-Kwakye, Fei Han, Alfred Adutwum Amponsah, Qing-Hua Ling, Timothy Apasiba Abeo:
A diversity enhanced hybrid particle swarm optimization and crow search algorithm for feature selection. Appl. Intell. 53(17): 20535-20560 (2023) - [j36]Shu-Jun Ji, Qing-Hua Ling, Fei Han:
An improved algorithm for small object detection based on YOLO v4 and multi-scale contextual information. Comput. Electr. Eng. 105: 108490 (2023) - [j35]Xiang Bao, Fei Han, Qing-Hua Ling, Yan-Qiong Ren:
A multi-instance multi-label learning algorithm based on radial basis functions and multi-objective particle swarm optimization. Intell. Data Anal. 27(6): 1681-1698 (2023) - [j34]Zhe Liu, Fei Han, Qinghua Ling, Henry Han, Jing Jiang:
A many-objective optimization evolutionary algorithm based on hyper-dominance degree. Swarm Evol. Comput. 83: 101411 (2023) - 2022
- [j33]Fei Han, Mingpeng Zheng, Qinghua Ling:
An improved multiobjective particle swarm optimization algorithm based on tripartite competition mechanism. Appl. Intell. 52(5): 5784-5816 (2022) - [j32]Jeremiah Osei-Kwakye, Fei Han, Alfred Adutwum Amponsah, Qinghua Ling, Timothy Apasiba Abeo:
A hybrid optimization method by incorporating adaptive response strategy for Feedforward neural network. Connect. Sci. 34(1): 578-607 (2022) - [j31]Fei Han, Shaojun Zhu, Qinghua Ling, Henry Han, Hailong Li, Xinli Guo, Jiechuan Cao:
Gene-CWGAN: a data enhancement method for gene expression profile based on improved CWGAN-GP. Neural Comput. Appl. 34(19): 16325-16339 (2022) - [j30]Jing Jiang, Fei Han, Jie Wang, Qinghua Ling, Henry Han, Yue Wang:
A two-stage evolutionary algorithm for large-scale sparse multiobjective optimization problems. Swarm Evol. Comput. 72: 101093 (2022) - 2021
- [j29]Alfred Adutwum Amponsah, Fei Han, Qing-Hua Ling, Patrick Kwaku Kudjo:
An enhanced class topper algorithm based on particle swarm optimizer for global optimization. Appl. Intell. 51(2): 1022-1040 (2021) - [j28]Alfred Adutwum Amponsah, Fei Han, Jeremiah Osei-Kwakye, Ernest Bonah, Qing-Hua Ling:
An improved multi-leader comprehensive learning particle swarm optimisation based on gravitational search algorithm. Connect. Sci. 33(4): 803-834 (2021) - [j27]Jing Jiang, Fei Han, Jie Wang, Qinghua Ling, Henry Han, Zizhu Fan:
Improving decomposition-based multiobjective evolutionary algorithm with local reference point aided search. Inf. Sci. 576: 557-576 (2021) - [j26]Fei Han, Wentao Chen, Qing-Hua Ling, Henry Han:
Multi-objective particle swarm optimization with adaptive strategies for feature selection. Swarm Evol. Comput. 62: 100847 (2021) - [c38]Mingjie Zhu, Fei Han:
Multi-objective Particle Swarm Optimization based on Space Decomposition for Feature Selection. CIS 2021: 387-391 - [c37]Shaojun Zhu, Fei Han:
A Data Enhancement Method for Gene Expression Profile Based on Improved WGAN-GP. NCAA 2021: 242-254 - 2020
- [j25]Arfan Ali Nagra, Fei Han, Qing-Hua Ling, Muhammad Abubaker, Farooq Ahmad, Sumet Mehta, Timothy Apasiba Abeo:
Hybrid self-inertia weight adaptive particle swarm optimisation with local search using C4.5 decision tree classifier for feature selection problems. Connect. Sci. 32(1): 16-36 (2020) - [j24]Zhe Liu, Fei Han, Qing-Hua Ling:
A novel particle swarm optimisation with mutation breeding. Connect. Sci. 32(4): 333-361 (2020) - [j23]Jing Jiang, Fei Han, Qinghua Ling, Jie Wang, Tiange Li, Henry Han:
Efficient network architecture search via multiobjective particle swarm optimization based on decomposition. Neural Networks 123: 305-316 (2020) - [c36]Sheng Fang, Fei Han, Wan-Yun Liang, Jing Jiang:
An Improved Conditional Generative Adversarial Network for Microarray Data. ICIC (1) 2020: 105-114 - [e1]Henry Han, Tie Wei, Wenbin Liu, Fei Han:
Recent Advances in Data Science - Third International Conference on Data Science, Medicine, and Bioinformatics, IDMB 2019, Nanning, China, June 22-24, 2019, Revised Selected Papers. Communications in Computer and Information Science 1099, Springer 2020, ISBN 978-981-15-8759-7 [contents]
2010 – 2019
- 2019
- [j22]Arfan Ali Nagra, Fei Han, Qing-Hua Ling, Sumet Mehta:
An Improved Hybrid Method Combining Gravitational Search Algorithm With Dynamic Multi Swarm Particle Swarm Optimization. IEEE Access 7: 50388-50399 (2019) - [j21]Tianhua Guan, Fei Han, Henry Han:
A Modified Multi-Objective Particle Swarm Optimization Based on Levy Flight and Double-Archive Mechanism. IEEE Access 7: 183444-183467 (2019) - [j20]Fei Han, Di Tang, Yu-Wen-Tian Sun, Zhun Cheng, Jing Jiang, Qiuwei Li:
A hybrid gene selection method based on gene scoring strategy and improved particle swarm optimization. BMC Bioinform. 20-S(8): 289:1-289:13 (2019) - [j19]Ying Xiong, Qing-Hua Ling, Fei Han, Qing-Hua Liu:
An efficient gene selection method for microarray data based on LASSO and BPSO. BMC Bioinform. 20-S(22): 715 (2019) - [j18]Qing-Hua Ling, Yuqing Song, Fei Han, Conghua Zhou, Hu Lu:
An improved learning algorithm for random neural networks based on particle swarm optimization and input-to-output sensitivity. Cogn. Syst. Res. 53: 51-60 (2019) - [j17]Fei Han, Jing Jiang, Qing-Hua Ling, Benyue Su:
A survey on metaheuristic optimization for random single-hidden layer feedforward neural network. Neurocomputing 335: 261-273 (2019) - [j16]Qing Liu, Franck Davoine, Jian Yang, Ying Cui, Zhong Jin, Fei Han:
A Fast and Accurate Matrix Completion Method Based on QR Decomposition and $L_{2, 1}$ -Norm Minimization. IEEE Trans. Neural Networks Learn. Syst. 30(3): 803-817 (2019) - [c35]Wentao Chen, Fei Han:
An Improved Multi-objective Particle Swarm Optimization with Adaptive Penalty Value for Feature Selection. BIC-TA (1) 2019: 649-661 - 2018
- [j15]Fei Han, Yu-Wen-Tian Sun, Qing-Hua Ling:
An Improved Multiobjective Quantum-Behaved Particle Swarm Optimization Based on Double Search Strategy and Circular Transposon Mechanism. Complex. 2018: 8702820:1-8702820:22 (2018) - [c34]Jing Jiang, Fei Han, Qing-Hua Ling, Benyue Su:
An Improved Evolutionary Extreme Learning Machine Based on Multiobjective Particle Swarm Optimization. ICIC (3) 2018: 1-6 - [c33]Qiuwei Li, Fei Han, Qinghua Ling:
An Improved Double Hidden-Layer Variable Length Incremental Extreme Learning Machine Based on Particle Swarm Optimization. ICIC (2) 2018: 34-43 - 2017
- [j14]Fei Han, Min-Ru Zhao, Jian-Ming Zhang, Qing-Hua Ling:
An improved incremental constructive single-hidden-layer feedforward networks for extreme learning machine based on particle swarm optimization. Neurocomputing 228: 133-142 (2017) - [j13]Fei Han, Chun Yang, Ya-Qi Wu, Jiansheng Zhu, Qing-Hua Ling, Yuqing Song, De-Shuang Huang:
A Gene Selection Method for Microarray Data Based on Binary PSO Encoding Gene-to-Class Sensitivity Information. IEEE ACM Trans. Comput. Biol. Bioinform. 14(1): 85-96 (2017) - [c32]Hongguan Liu, Fei Han:
A Modified Standard PSO-2011 with Robust Search Ability. BIC-TA 2017: 207-222 - [c31]Qing-Hua Ling, Yuqing Song, Fei Han, Hu Lu:
An Improved Evolutionary Random Neural Networks Based on Particle Swarm Optimization and Input-to-Output Sensitivity. ICIC (1) 2017: 121-127 - [c30]Yan Jiang, Fei Han:
A Hybrid Algorithm of Adaptive Particle Swarm Optimization Based on Adaptive Moment Estimation Method. ICIC (1) 2017: 658-667 - [c29]Pan-Pan Du, Fei Han:
An Improved Multi-swarm Particle Swarm Optimization Based on Knowledge Billboard and Periodic Search Mechanism. ICIC (1) 2017: 668-678 - [c28]Ning Lai, Fei Han:
A Hybrid Particle Swarm Optimization Algorithm Based on Migration Mechanism. IScIDE 2017: 88-100 - [c27]Hongfei Bao, Fei Han:
A Hybrid Multi-swarm PSO Algorithm Based on Shuffled Frog Leaping Algorithm. IScIDE 2017: 101-112 - 2016
- [c26]Jun He, Fei Han, Shoubao Su:
A Hybrid Particle Swarm Optimization Embedded Trust Region Method. ICIC (1) 2016: 762-771 - [c25]Ya-Qi Wu, Fei Han, Qing-Hua Ling:
An Improved Ensemble Extreme Learning Machine Based on ARPSO and Tournament-Selection. ICSI (2) 2016: 89-96 - 2015
- [c24]Fei Han, Min-Ru Zhao, Jian-Ming Zhang:
An Improved Incremental Error Minimized Extreme Learning Machine for Regression Problem Based on Particle Swarm Optimization. ICIC (3) 2015: 94-100 - [c23]Fei Han, Dan Yang, Qing-Hua Ling, De-Shuang Huang:
A novel diversity-guided ensemble of neural network based on attractive and repulsive particle swarm optimization. IJCNN 2015: 1-7 - [c22]Fei Han, Qing Liu:
An Improved Hybrid PSO Based on ARPSO and the Quasi-Newton Method. ICSI (1) 2015: 460-467 - 2014
- [j12]Fei Han, Qing Liu:
A diversity-guided hybrid particle swarm optimization based on gradient search. Neurocomputing 137: 234-240 (2014) - [c21]Dan Yang, Fei Han:
An Improved Ensemble of Extreme Learning Machine Based on Attractive and Repulsive Particle Swarm Optimization. ICIC (1) 2014: 213-220 - [c20]Fei Han, Ya-Qi Wu, Yu Cui:
A Hybrid Approach for Cancer Classification Based on Particle Swarm Optimization and Prior Information. ICSI (1) 2014: 350-356 - [c19]Min-Ru Zhao, Jian-Ming Zhang, Fei Han:
An improved extreme learning machine with adaptive growth of hidden nodes based on particle swarm optimization. IJCNN 2014: 886-890 - 2013
- [j11]Fei Han, Jiansheng Zhu:
Improved Particle Swarm Optimization Combined with Backpropagation for Feedforward Neural Networks. Int. J. Intell. Syst. 28(3): 271-288 (2013) - [j10]Fei Han, Hai-Fen Yao, Qing-Hua Ling:
An improved evolutionary extreme learning machine based on particle swarm optimization. Neurocomputing 116: 87-93 (2013) - [j9]Xiaobo Chen, Jian Yang, Qirong Mao, Fei Han:
Regularized least squares fisher linear discriminant with applications to image recognition. Neurocomputing 122: 521-534 (2013) - [c18]Qing Liu, Fei Han:
A Hybrid Attractive and Repulsive Particle Swarm Optimization Based on Gradient Search. ICIC (2) 2013: 155-162 - [c17]Xiaobo Chen, Qirong Mao, Fei Han, Jun Liang:
Improved twin support vector machine using total margin and graph embedding. ICNC 2013: 39-43 - 2012
- [c16]Fei Han, Qing Liu:
A Diversity-Guided Hybrid Particle Swarm Optimization. ICIC (3) 2012: 461-466 - 2011
- [c15]Fei Han, Hai-Fen Yao, Qing-Hua Ling:
An Improved Extreme Learning Machine Based on Particle Swarm Optimization. ICIC (3) 2011: 699-704 - [c14]Fei Han, Jiansheng Zhu:
An improved ARPSO for feedforward neural networks. ICNC 2011: 1146-1150 - 2010
- [j8]Fei Han, Qing-Hua Ling, De-Shuang Huang:
An improved approximation approach incorporating particle swarm optimization and a priori information into neural networks. Neural Comput. Appl. 19(2): 255-261 (2010) - [c13]Yu Cui, Fei Han, Shiguang Ju:
Gene Selection and PSO-BP Classifier Encoding a Prior Information. ICSI (2) 2010: 335-342
2000 – 2009
- 2009
- [c12]Yu Cui, Shiguang Ju, Fei Han, Tong-Yue Gu:
An Improved Approach Combining Random PSO with BP for Feedforward Neural Networks. AICI 2009: 361-368 - [c11]Tong-Yue Gu, Shiguang Ju, Fei Han:
An Improved PSO Algorithm Encoding a priori Information for Nonlinear Approximation. ICIC (2) 2009: 223-231 - [c10]Qing-Hua Ling, Fei Han:
A Constrained Approximation Algorithm by Encoding Second-Order Derivative Information into Feedforward Neural Networks. ICIC (2) 2009: 928-934 - [c9]Tong-Yue Gu, Shiguang Ju, Fei Han:
A PSO Algorithm with the Improved Diversity for Feedforward Neural Networks. IITSI 2009: 123-127 - 2008
- [j7]Fei Han, Qing-Hua Ling:
A new approach for function approximation incorporating adaptive particle swarm optimization and a priori information. Appl. Math. Comput. 205(2): 792-798 (2008) - [j6]Fei Han, Qing-Hua Ling, De-Shuang Huang:
Modified constrained learning algorithms incorporating additional functional constraints into neural networks. Inf. Sci. 178(3): 907-919 (2008) - [j5]Fei Han, De-Shuang Huang:
A new constrained learning algorithm for function approximation by encoding a priori information into feedforward neural networks. Neural Comput. Appl. 17(5-6): 433-439 (2008) - [c8]Fei Han, Tong-Yue Gu, Qing-Hua Ling:
A New Approach Encoding a Priori Information for Function Approximation. CSSE (1) 2008: 82-85 - [c7]Fei Han:
Improved Learning Algorithms of SLFN for Approximating Periodic Function. ICIC (2) 2008: 654-660 - 2007
- [c6]Fei Han, Qing-Hua Ling:
A New Learning Algorithm for Function Approximation by Encoding Additional Constraints into Feedforward Neural Network. ICIC (3) 2007: 64-72 - [c5]Fei Han, Qing-Hua Ling:
A New Learning Algorithm for Function Approximation By Incorporating A Priori Information Into Feedforward Neural Networks. ICNC (1) 2007: 29-33 - [c4]Fei Han, Qing-Hua Ling:
A New Approach for Function Approximation Based on Adaptive Particle Swarm Optimization. ICNC (4) 2007: 501-505 - 2006
- [j4]Fei Han, De-Shuang Huang:
Improved constrained learning algorithms by incorporating additional functional constraints into neural networks. Appl. Math. Comput. 174(1): 34-50 (2006) - [j3]Fei Han, De-Shuang Huang, Zhi-Hua Zhu, Tie-Hua Rong:
The Forecast of the Postoperative Survival Time of Patients Suffered from Non-small Cell Lung Cancer Based on Pca and Extreme Learning Machine. Int. J. Neural Syst. 16(1): 39-46 (2006) - [j2]Fei Han, De-Shuang Huang:
Improved extreme learning machine for function approximation by encoding a priori information. Neurocomputing 69(16-18): 2369-2373 (2006) - [j1]Fei Han, Xu-Qin Li, Michael R. Lyu, Tat-Ming Lok:
A modified learning algorithm incorporating additional functional constraints into neural networks. Int. J. Pattern Recognit. Artif. Intell. 20(2): 129-142 (2006) - [c3]Fei Han, Tat-Ming Lok, Michael R. Lyu:
A New Learning Algorithm for Function Approximation Incorporating A Priori Information into Extreme Learning Machine. ISNN (1) 2006: 631-636 - 2005
- [c2]Xu-Qin Li, Fei Han, Tat-Ming Lok, Michael R. Lyu, Guang-Bin Huang:
Improvements to the Conventional Layer-by-Layer BP Algorithm. ICIC (2) 2005: 189-198 - [c1]Fei Han, Deshuang Huang, Yiu-ming Cheung, Guang-Bin Huang:
A New Modified Hybrid Learning Algorithm for Feedforward Neural Networks. ISNN (1) 2005: 572-577
Coauthor Index
Qing-Hua Ling
aka: Qinghua Ling
aka: Qinghua Ling
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