化工学报2016，Vol.67Issue(3)：998-1007,10.DOI:10.11949/j.issn.0438-1157.20151922
基于改进PDF技术的间歇过程NFM模型
Improved PDF technology based NFM for batch process
摘要
Abstract
Batch process is an typical nolinear production process and can be simulated by a neuro-fuzzy model (NFM). In the previous research, a new model training method called PDF technology was proposed to successfully conquer the weak generalization ability which caused by the MSE rule based model training. But the density function is hard to estimate and the trained model are not stable when the target PDF can not given. To solve these problems, a new window width estimation method is introduced and also a contraction strategy with a PDF predictor is proposed when the target can not be given. Simulation results demonstrate that the proposed methods can get a more accurate density estimation and a more excellent model prediction ability.关键词
间歇过程/神经模糊模型/概率密度函数/收缩策略/算法/预测Key words
batch process/neuro-fuzzy model/probability density function/contraction strategy/algorithm/prediction分类
信息技术与安全科学引用本文复制引用
付钊,贾立..基于改进PDF技术的间歇过程NFM模型[J].化工学报,2016,67(3):998-1007,10.基金项目
国家自然科学基金项目（61374044）；上海市科委国际合作项目（12510709400)；上海市教委创新重点项目（14ZZ088）；2013年度上海市人才发展基金项目。@@@@supported by the National Natural Science Foundation of China (61374044), the Shanghai Science Technology Commission (12510709400), the Shanghai Municipal Education Commission (14ZZ088) and the Shanghai Talent Development Plan 2013 （61374044）
