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ORCIDShuiming Zhong
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2020 – today
- 2024
[j13]Shuiming Zhong
, Huan Lyu, Xiaoxiang Lu, Baowei Wang, Dingcheng Wang:
A New Sufficient & Necessary Condition for Testing Linear Separability Between Two Sets. IEEE Trans. Pattern Anal. Mach. Intell. 46(6): 4160-4173 (2024)
2010 – 2019
- 2018
- [c4]Shuiming Zhong, Xiaoxiang Lu, Meng Li, Chengguang Liu, Yong Cheng, Victor S. Sheng:
An Adaptive Construction Test Method Based on Geometric Calculation for Linearly Separable Problems. ICCCS (6) 2018: 392-405 - 2017
- [j12]Yan Xu, Jing Yang, Shuiming Zhong:
An online supervised learning method based on gradient descent for spiking neurons. Neural Networks 93: 7-20 (2017) - 2016
- [j11]Zhan Shi, Xiaoqin Zeng, Tingting Zhang, Song Huang, Zekun Qi, Hui Li, Bin Hu, Yi Yao, Shuiming Zhong:
Bidirectional transformation between BPMN and BPEL with graph grammar. Comput. Electr. Eng. 51: 304-319 (2016) - 2015
- [j10]Yu Xue, Shuiming Zhong, Tinghuai Ma, Jie Cao:
A Hybrid Evolutionary Algorithm for Numerical Optimization Problem. Intell. Autom. Soft Comput. 21(4): 473-490 (2015) - 2014
- [j9]Yu Xue, Shuiming Zhong, Yi Zhuang, Bin Xu:
An ensemble algorithm with self-adaptive learning techniques for high-dimensional numerical optimization. Appl. Math. Comput. 231: 329-346 (2014) - [j8]Lihong Huang, Xiaoqin Zeng, Shuiming Zhong, Lixin Han:
Sensitivity study of Binary Feedforward Neural Networks. Neurocomputing 136: 268-280 (2014) - [j7]Yu Xue, Xiangmao Chang, Shuiming Zhong, Yi Zhuang:
An efficient energy hole alleviating algorithm for wireless sensor networks. IEEE Trans. Consumer Electron. 60(3): 347-355 (2014) - 2013
- [j6]Jing Yang, Xiaoqin Zeng, Shuiming Zhong:
Computation of multilayer perceptron sensitivity to input perturbation. Neurocomputing 99: 390-398 (2013) - [j5]Yan Xu, Xiaoqin Zeng, Shuiming Zhong:
A New Supervised Learning Algorithm for Spiking Neurons. Neural Comput. 25(6): 1472-1511 (2013) - [j4]Jing Yang, Xiaoqin Zeng, Shuiming Zhong, Shengli Wu:
Effective Neural Network Ensemble Approach for Improving Generalization Performance. IEEE Trans. Neural Networks Learn. Syst. 24(6): 878-887 (2013) - 2012
- [j3]Shuiming Zhong, Xiaoqin Zeng, Shengli Wu, Lixin Han:
Sensitivity-Based Adaptive Learning Rules for Binary Feedforward Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 23(3): 480-491 (2012) - 2010
- [j2]Shuiming Zhong, Xiaoqin Zeng, Huiyi Liu, Yan Xu:
Approximate computation of Madaline sensitivity based on discrete stochastic technique. Sci. China Inf. Sci. 53(12): 2399-2414 (2010) - [c3]Xianming Chen, Xiaoqin Zeng, Rong Chu, Shuiming Zhong:
A quantified sensitivity measure of Radial Basis Function Neural Networks to input variation. IJCNN 2010: 1-6
2000 – 2009
- 2009
- [j1]Xiaoqin Zeng, Jing Shao, Yingfeng Wang, Shuiming Zhong:
A sensitivity-based approach for pruning architecture of Madalines. Neural Comput. Appl. 18(8): 957-965 (2009) - [c2]Yanjun Liu, Xiaoqin Zeng, Shuiming Zhong, Shengli Wu:
A Sensitivity-Based Training Algorithm with Architecture Adjusting for Madalines. SMC 2009: 4586-4591 - 2008
- [c1]Lei Lu, Xiaoqin Zeng, Shengli Wu, Shuiming Zhong:
A Novel Ensemble Approach for Improving Generalization Ability of Neural Networks. IDEAL 2008: 164-171
Coauthor Index
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