化工学报2019，Vol.70Issue(7)：2606-2615,10.DOI:10.11949/j.issn.0438-1157.20190180
基于混合评价指标的自组织模糊神经网络设计研究
Design of self-organizing fuzzy neural network based on hybrid evaluation index
摘要
Abstract
Aiming at the problem that the fuzzy neural network structure is difficult to adapt when there is no growth and pruning thresholds, this paper proposes a structure design method based on hybrid evaluation index (HEI). First, the initial number, centers and widths of rule neurons are determined by the fuzzy C-means clustering algorithm. Next, a novel relevance evaluation index (REI), which is composed of the Davies bouldin index (DBI) and the Dunn index (DI), is presented to calculate the correlation among the outputs of rule neurons. The learning ability of neural network will be determined by the change of root mean square error (RMSE) during the training process. Then, the HEI is presented based on REI and RMSE. The topology structure of the fuzzy neural network is adjusted according to the HEI. Finally, the feasibility and effectiveness of the structure design method are proved by using the Mackey-Glass time series prediction, nonlinear system identification and PM2.5 concentration prediction.关键词
自组织模糊神经网络/混合评价指标/优化设计/动态建模/预测Key words
self-organizing fuzzy neural network/hybrid evaluation index (HEI)/optimal design/dynamic modeling/prediction分类
信息技术与安全科学引用本文复制引用
QIAO Junfei,HE Zengzeng,DU Shengli..基于混合评价指标的自组织模糊神经网络设计研究[J].化工学报,2019,70(7):2606-2615,10.基金项目
国家自然科学基金项目(61533002, 61603012, 61603009) （61533002, 61603012, 61603009）
北京市教委项目(KM201710005025) （KM201710005025）
中国博士后科学基金项目(2017M620555) （2017M620555）
