基于粗糙-模糊推理系统的化工过程建模研究  

RESEARCH OF CHEMICAL MODELING METHOD BASED ON ROUGH-FUZZY INFERENCE SYSTEM

作　　者：毕利[1] 高利娟[1] 

机构地区：[1]宁夏大学数学计算机学院,化学化工学院,宁夏银川750021

出　　处：《计算机应用与软件》2011年第2期56-59,共4页Computer Applications and Software

基　　金：国家科技支撑计划基金项目子课题(2007BAA08B0502)

摘　　要：根据粗糙集方法所导出的规则构造模糊—神经网络,由规则的参数和离散化结果估计网络参数的初始值,使网络经训练能较快收敛并达到最优值。将其应用于PTA装置溶剂脱水塔精馏过程建模,所建模型的性能优于普通前馈神经网络,粗糙—模糊神经网络可以消除决策系统的冗余信息,降低模型复杂度。In the paper we construct a fuzzy neural network based on the rule derived from rough sets method.The initial value of the network parameter is estimated by rule parameter and discretisation results,this makes the trained network be able to converge faster and achieve optimum.It has been applied to modelling the solvent dehydrating tower in PTA complex process,the performance of the model outperforms the common feed-forward neural network.The fuzzy neural network can eliminate redundant information of decision-making system and reduce model＇s complexity.

关 键 词：数据挖掘 神经网络 模糊系统 粗糙集 化工建模 

分 类 号：TP273.4[自动化与计算机技术—检测技术与自动化装置]