智能系统学报Issue(4)：327-332,6.DOI:10.3969/j.issn.1673-4785.201305026
一种优化神经网络的教与学优化算法
A modified teaching-learning-based optimization algorithm and application in neural networks
摘要
Abstract
In order to improve the output accuracy of back propagation neural network, a modified teaching-learn-ing-based optimization ( MTLBO) algorithm is proposed to train the weight and threshold value of neural network. In the MTLBO method, the “Teaching” phase and “Learning” phase were modified on the basis of TLBO algorithm, and a new “Self-Learning” mechanism was proposed to intensify global searching ability. Finally, the function fit-ting experiment and the tractor gearbox diagnosis experiment were used to test the performance of the proposed algo-rithm. Simulations show that this algorithm has a better convergence, prediction accuracy and robustness compared to the genetic algorithm ( GA) and the basic teaching-learning-based optimization ( TLBO) algorithm.关键词
改进的教与学优化算法/“自学”机制/神经网络/函数拟合/齿轮箱故障诊断Key words
modified teaching-learning-based optimization algorithm/“self-learning” mechanism/neural network/function fitting/gearbox fault diagnosis分类
信息技术与安全科学引用本文复制引用
拓守恒..一种优化神经网络的教与学优化算法[J].智能系统学报,2013,(4):327-332,6.基金项目
陕西省教育厅科研计划资助项目（12JK0863）；陕西理工科研项目（ SLGKY 12-16）． （）
