四川大学学报（自然科学版）2017，Vol.54Issue(5)：978-984,7.DOI:10.3969/j.issn.0490-6756.2017.05.014
基于自适应动量因子的区间神经网络建模方法
Interval neural network modeling method based on adaptive momentum factor
摘要
Abstract
The modeling of interval neural network is not only a component of interval control,but also an important role to improve the robust of systems.An adaptive algorithm of momentum factor is proposed to solve the problem of slow convergence speed on the interval neural network.In this paper,interval calculation method is used to establish the mapping model of input and output variables.By introducing a momentum term with adaptive characteristics,the steepest descent algorithm is applied to update the adaptive momentum factor.Compared with the traditional method,this method not only accelerates the convergence speed,but also overcome the disadvantages of the system steady state error and easily to fall into local minimum.According to the nonlinear experiments,interval neural networks are able to establish the zone models,and the algorithm of adaptive momentum factor increase the overall performance of the network.Classic bench mark experiments show that our work can more accurate to establish interval network model,while introducing of adaptive momentum factor algorithm also can improve the overall performance of the interval neural network.关键词
区间控制/区间神经网络/动量因子/自适应Key words
Interval control/Interval neural network/Momentum factor/Modeling分类
信息技术与安全科学引用本文复制引用
陈实,易军,李倩,黄迪,李太福..基于自适应动量因子的区间神经网络建模方法[J].四川大学学报（自然科学版）,2017,54(5):978-984,7.基金项目
国家自然科学基金(51375520,51374268,51404051,61174015) （51375520,51374268,51404051,61174015）
重庆市重大应用技术开发项目(cstc2013yykfC0034) （cstc2013yykfC0034）
重庆市优秀人才科技训练计划(cstc2013kjrc-qnrc40008) （cstc2013kjrc-qnrc40008）
重庆市高校创新团队项目(KJTD201324) （KJTD201324）
重庆市高校优秀成果转化项目(KJZH14218) （KJZH14218）
重庆市基础科学与前沿技术研究(cstc2015jcyjBX0099) （cstc2015jcyjBX0099）
重庆科技学院研究生科技创新计划项目基金(YKJCX1620402) （YKJCX1620402）
