Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
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)
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
Journal Articles
- 2023
[j37]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)- [j36]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) - [j35]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) - [j34]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) - [j33]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
- [j32]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) - [j31]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) - [j30]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) - [j29]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
- [j28]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) - [j27]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) - [j26]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) - [j25]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) - 2020
- [j24]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) - [j23]Zhe Liu, Fei Han, Qing-Hua Ling:
A novel particle swarm optimisation with mutation breeding. Connect. Sci. 32(4): 333-361 (2020) - [j22]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) - 2019
- [j21]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) - [j20]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) - [j19]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) - [j18]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) - [j17]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) - [j16]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) - [j15]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) - 2018
- [j14]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) - 2017
- [j13]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) - [j12]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) - 2014
- [j11]Fei Han, Qing Liu:
A diversity-guided hybrid particle swarm optimization based on gradient search. Neurocomputing 137: 234-240 (2014) - 2013
- [j10]Fei Han, Jiansheng Zhu:
Improved Particle Swarm Optimization Combined with Backpropagation for Feedforward Neural Networks. Int. J. Intell. Syst. 28(3): 271-288 (2013) - [j9]Fei Han, Hai-Fen Yao, Qing-Hua Ling:
An improved evolutionary extreme learning machine based on particle swarm optimization. Neurocomputing 116: 87-93 (2013) - 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) - 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) - 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)
Conference and Workshop Papers
- 2021
- [c37]Mingjie Zhu, Fei Han:
Multi-objective Particle Swarm Optimization based on Space Decomposition for Feature Selection. CIS 2021: 387-391 - [c36]Shaojun Zhu, Fei Han:
A Data Enhancement Method for Gene Expression Profile Based on Improved WGAN-GP. NCAA 2021: 242-254 - 2020
- [c35]Sheng Fang, Fei Han, Wan-Yun Liang, Jing Jiang:
An Improved Conditional Generative Adversarial Network for Microarray Data. ICIC (1) 2020: 105-114 - 2019
- [c34]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
- [c33]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 - [c32]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
- [c31]Hongguan Liu, Fei Han:
A Modified Standard PSO-2011 with Robust Search Ability. BIC-TA 2017: 207-222 - [c30]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 - [c29]Yan Jiang, Fei Han:
A Hybrid Algorithm of Adaptive Particle Swarm Optimization Based on Adaptive Moment Estimation Method. ICIC (1) 2017: 658-667 - [c28]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 - [c27]Ning Lai, Fei Han:
A Hybrid Particle Swarm Optimization Algorithm Based on Migration Mechanism. IScIDE 2017: 88-100 - [c26]Hongfei Bao, Fei Han:
A Hybrid Multi-swarm PSO Algorithm Based on Shuffled Frog Leaping Algorithm. IScIDE 2017: 101-112 - 2016
- [c25]Jun He, Fei Han, Shoubao Su:
A Hybrid Particle Swarm Optimization Embedded Trust Region Method. ICIC (1) 2016: 762-771 - [c24]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
- [c23]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 - [c22]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 - [c21]Fei Han, Qing Liu:
An Improved Hybrid PSO Based on ARPSO and the Quasi-Newton Method. ICSI (1) 2015: 460-467 - 2014
- [c20]Dan Yang, Fei Han:
An Improved Ensemble of Extreme Learning Machine Based on Attractive and Repulsive Particle Swarm Optimization. ICIC (1) 2014: 213-220 - [c19]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 - [c18]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
- [c17]Qing Liu, Fei Han:
A Hybrid Attractive and Repulsive Particle Swarm Optimization Based on Gradient Search. ICIC (2) 2013: 155-162 - 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
- [c13]Yu Cui, Fei Han, Shiguang Ju:
Gene Selection and PSO-BP Classifier Encoding a Prior Information. ICSI (2) 2010: 335-342 - 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
- [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
- [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
Editorship
- 2020
- [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]
Coauthor Index
Qing-Hua Ling
aka: Qinghua Ling
aka: Qinghua Ling
a service of 
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-06-10 23:05 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
