According to our database1, Shuiming Zhong authored at least 16 papers between 2008 and 2018.
Legend:Book In proceedings Article PhD thesis Other
An Adaptive Construction Test Method Based on Geometric Calculation for Linearly Separable Problems.
Proceedings of the Cloud Computing and Security - 4th International Conference, 2018
An online supervised learning method based on gradient descent for spiking neurons.
Neural Networks, 2017
Bidirectional transformation between BPMN and BPEL with graph grammar.
Computers & Electrical Engineering, 2016
A Hybrid Evolutionary Algorithm for Numerical Optimization Problem.
Intelligent Automation & Soft Computing, 2015
An efficient energy hole alleviating algorithm for wireless sensor networks.
IEEE Trans. Consumer Electronics, 2014
Sensitivity study of Binary Feedforward Neural Networks.
An ensemble algorithm with self-adaptive learning techniques for high-dimensional numerical optimization.
Applied Mathematics and Computation, 2014
Effective Neural Network Ensemble Approach for Improving Generalization Performance.
IEEE Trans. Neural Netw. Learning Syst., 2013
A New Supervised Learning Algorithm for Spiking Neurons.
Neural Computation, 2013
Computation of multilayer perceptron sensitivity to input perturbation.
Sensitivity-Based Adaptive Learning Rules for Binary Feedforward Neural Networks.
IEEE Trans. Neural Netw. Learning Syst., 2012
Approximate computation of Madaline sensitivity based on discrete stochastic technique.
SCIENCE CHINA Information Sciences, 2010
A quantified sensitivity measure of Radial Basis Function Neural Networks to input variation.
Proceedings of the International Joint Conference on Neural Networks, 2010
A sensitivity-based approach for pruning architecture of Madalines.
Neural Computing and Applications, 2009
A Sensitivity-Based Training Algorithm with Architecture Adjusting for Madalines.
Proceedings of the IEEE International Conference on Systems, 2009
A Novel Ensemble Approach for Improving Generalization Ability of Neural Networks.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2008