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Yanhong Feng
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2020 – today
- 2022
- [j21]Yanhong Feng, Gai-Ge Wang:
A binary moth search algorithm based on self-learning for multidimensional knapsack problems. Future Gener. Comput. Syst. 126: 48-64 (2022) - 2021
- [j20]Yanhong Feng, Suash Deb, Gai-Ge Wang, Amir Hossein Alavi:
Monarch butterfly optimization: A comprehensive review. Expert Syst. Appl. 168: 114418 (2021) - 2020
- [j19]Congcong Wu, Jianli Zhao, Yanhong Feng, Malrey Lee:
"Solving discounted {0-1} knapsack problems by a discrete hybrid teaching-learning-based optimization algorithm". Appl. Intell. 50(6): 1872-1888 (2020)
2010 – 2019
- 2019
- [j18]Yanhong Feng, Jiao-Hong Yi, Gai-Ge Wang:
Enhanced Moth Search Algorithm for the Set-Union Knapsack Problems. IEEE Access 7: 173774-173785 (2019) - [j17]Zhongfu Wang, Yanhong Feng:
Evaluation model of economic competitiveness based on multi-layer fuzzy neural network. Clust. Comput. 22(Supplement): 4405-4412 (2019) - [j16]Yanhong Feng, Zhongfu Wang:
Improved data envelopment analysis model based on geometric mean model. Int. J. Comput. Appl. Technol. 61(1/2): 8-15 (2019) - [j15]Yanhong Feng, Zhongfu Wang:
Development mode of circular economy industrial cluster based on game theory. Int. J. Comput. Appl. Technol. 61(1/2): 47-53 (2019) - [j14]Yanhong Feng, Zhongfu Wang:
Innovation mechanism of cluster industry based on weighted time-varying multi-criteria and similarity evaluation method. Int. J. Comput. Appl. Technol. 61(1/2): 135-141 (2019) - 2018
- [j13]Yanhong Feng, Gai-Ge Wang:
Binary Moth Search Algorithm for Discounted {0-1} Knapsack Problem. IEEE Access 6: 10708-10719 (2018) - [j12]Yanhong Feng, Gai-Ge Wang, Junyu Dong, Ling Wang:
Opposition-based learning monarch butterfly optimization with Gaussian perturbation for large-scale 0-1 knapsack problem. Comput. Electr. Eng. 67: 454-468 (2018) - [j11]Yanhong Feng, Gai-Ge Wang, Ling Wang:
Solving randomized time-varying knapsack problems by a novel global firefly algorithm. Eng. Comput. 34(3): 621-635 (2018) - [j10]Yanhong Feng, Hong Yu, Geng Sun, Juanjuan Sun:
基于BLSTM的命名实体识别方法 (Named Entity Recognition Method Based on BLSTM). 计算机科学 45(2): 261-268 (2018) - [j9]Yanhong Feng, Hong Yu, Geng Sun, Song Peng:
基于非对称多值特征杰卡德系数的高维语义向量差异性度量方法 (Diversity Measures Method in High-dimensional Semantic Vector Based on Asymmetric Multi-valued Feature Jaccard Coefficient). 计算机科学 45(6): 57-66 (2018) - [j8]Yanhong Feng, Juan Yang, Congcong Wu, Mei Lu, Xiang-Jun Zhao:
Solving 0-1 knapsack problems by chaotic monarch butterfly optimization algorithm with Gaussian mutation. Memetic Comput. 10(2): 135-150 (2018) - [j7]Yanhong Feng, Gai-Ge Wang, Wenbin Li, Ning Li:
Multi-strategy monarch butterfly optimization algorithm for discounted {0-1} knapsack problem. Neural Comput. Appl. 30(10): 3019-3036 (2018) - 2017
- [j6]Yanhong Feng, Gai-Ge Wang, Suash Deb, Mei Lu, Xiang-Jun Zhao:
Solving 0-1 knapsack problem by a novel binary monarch butterfly optimization. Neural Comput. Appl. 28(7): 1619-1634 (2017) - 2016
- [j5]Yanhong Feng, Gai-Ge Wang, Xiao-Zhi Gao:
A Novel Hybrid Cuckoo Search Algorithm with Global Harmony Search for 0-1 Knapsack Problems. Int. J. Comput. Intell. Syst. 9(6): 1174-1190 (2016) - 2014
- [j4]Yanhong Feng, Gai-Ge Wang, Qingjiang Feng, Xiang-Jun Zhao:
An Effective Hybrid Cuckoo Search Algorithm with Improved Shuffled Frog Leaping Algorithm for 0-1 Knapsack Problems. Comput. Intell. Neurosci. 2014: 857254:1-857254:17 (2014) - [j3]Yanhong Feng, Ke Jia, Yichao He:
An Improved Hybrid Encoding Cuckoo Search Algorithm for 0-1 Knapsack Problems. Comput. Intell. Neurosci. 2014: 970456:1-970456:9 (2014) - [j2]Yingchun Guo, Yanhong Feng, Gang Yan, Shuo Shi:
Multi-Resolution Salient Region Detection in Frequency Domain. Int. J. Adv. Pervasive Ubiquitous Comput. 6(1): 60-70 (2014)
2000 – 2009
- 2001
- [j1]Martha S. Head, M. Dominic Ryan, Dennis Lee, Yanhong Feng, Cheryl A. Janson, Nestor O. Concha, Paul M. Keller, Walter E. deWolf Jr.:
Structure-based combinatorial library design: Discovery of non-peptidic inhibitors of caspases 3 and 8. J. Comput. Aided Mol. Des. 15(12): 1105-1117 (2001)
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