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Qing-Hua Ling
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2024
- [j30]Fei Han, Fanyu Li, Qinghua Ling, Henry Han, Tianyi Lu, Zijian Jiao, Haonan Zhang:
A Feature Selection Method Based on Feature-Label Correlation Information and Self-Adaptive MOPSO. Neural Process. Lett. 56(2): 110 (2024) - [j29]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) - 2023
- [j28]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) - [j27]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) - [j26]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) - [j25]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) - [j24]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
- [j23]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) - [j22]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) - [j21]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) - [j20]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) - [j19]Qing-Hua Ling, Zhi-Hao Tang, Gan Huang, Fei Han:
An Improved Multi-Objective Particle Swarm Optimization Algorithm Based on Angle Preference. Symmetry 14(12): 2619 (2022) - 2021
- [j18]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) - [j17]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) - [j16]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) - [j15]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
- [j14]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) - [j13]Zhe Liu
, Fei Han, Qing-Hua Ling:
A novel particle swarm optimisation with mutation breeding. Connect. Sci. 32(4): 333-361 (2020) - [j12]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)
2010 – 2019
- 2019
- [j11]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) - [j10]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) - [j9]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) - [j8]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) - 2018
- [j7]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) - [c12]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 - [c11]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
- [j6]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) - [j5]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) - [c10]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 - 2016
- [c9]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
- [c8]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 - 2013
- [j4]Fei Han, Hai-Fen Yao, Qing-Hua Ling:
An improved evolutionary extreme learning machine based on particle swarm optimization. Neurocomputing 116: 87-93 (2013) - 2011
- [c7]Fei Han, Hai-Fen Yao, Qing-Hua Ling:
An Improved Extreme Learning Machine Based on Particle Swarm Optimization. ICIC (3) 2011: 699-704 - 2010
- [j3]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)
2000 – 2009
- 2009
- [c6]Qing-Hua Ling, Fei Han:
A Constrained Approximation Algorithm by Encoding Second-Order Derivative Information into Feedforward Neural Networks. ICIC (2) 2009: 928-934 - 2008
- [j2]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) - [j1]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) - [c5]Fei Han, Tong-Yue Gu, Qing-Hua Ling:
A New Approach Encoding a Priori Information for Function Approximation. CSSE (1) 2008: 82-85 - 2007
- [c4]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 - [c3]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 - [c2]Fei Han, Qing-Hua Ling:
A New Approach for Function Approximation Based on Adaptive Particle Swarm Optimization. ICNC (4) 2007: 501-505 - 2005
- [c1]Qing-Hua Ling, Max Q.-H. Meng, Tao Mei, Haoran Lu:
3D simulation design based on openGL for four-legged robot. ROBIO 2005: 713-717
Coauthor Index
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