Simulation and Off-line Optimization of an Acrylonitrile Fluidized-bed Reactor Based on Artificial Neural Network  

作　　者：李伟 张述伟 李燕 张沛存 王效斗 

机构地区：[1]School of Chemical Engineering, Dalian University of Technology, Dalian 116012,ChinaZHANG Peicun, WANG XiaodouQilu Petrochemical Corporation, SINOPEC, Zibo 255068,China [2]Qilu Petrochemical Corporation,SINOPEC,Zibo 255068,China

出　　处：《Chinese Journal of Chemical Engineering》2002年第2期198-201,共4页中国化学工程学报（英文版）

摘　　要：A mathematical model is developed for an industrial acrylonitrile fluidized-bed reactor based on arti-ficial neural networks. A new algorithm, which combines the characteristics of both genetic algorithm (GA) andgeneralized delta-rule (GDR) is used to train artificial neural network (ANN) in order to avoid search terminatedat a local optimal solution. For searching the global optimum, a new algorithm called SM-GA, incorporating ad-vantages of both simplex method (SM)and GA, is proposed and applied to optimize the operating conditions of anacrylonitrile fluidized-bed reactor in industry.A mathematical model is developed for an industrial acrylonitrile fluidized-bed reactor based on artificial neural networks. A new algorithm, which combines the characteristics of both genetic algorithm (GA) and generalized delta-rule (GDR) is used to train artificial neural network (ANN) in order to avoid search terminated at a local optimal solution. For searching the global optimum, a new algorithm called SM-GA, incorporating advantages of both simplex method (SM )and GA, is proposed and applied to optimize the operating conditions of an acrylonitrile fluidized-bed reactor in industry.

关 键 词：SIMULATION OPTIMIZATION artificial neural network genetic algorithm simplex method fluidized-bed reactor ACRYLONITRILE 

分 类 号：TQ226[化学工程—有机化工]