节点文献
基于神经网络模型的混沌优化及其应用
Chaos Optimization Based on Neural Network Model and Its Application
【摘要】 研究一种新型优化算法———混沌优化 ,提出加快解的收敛速度和精度新方法 ,并与精确不可微罚函数结合来求解非线性约束优化问题。对不能用数学解析式精确表达的优化问题利用神经网络建模 ,在此基础上进行混沌搜索寻优。该方法应用于甲醛生产过程的稳态优化 ,获得较好的经济效益。
【Abstract】 Chaos optimization method combined with exact nondifferentiable penalty function is proposed for solving nonlinear constraint optimization problems,and linear search is applied to speed the rate of convergence and improve the accuracy of solution.To solve the problem of establishing process staticstate model,artificial neural network is proposed.This method is applied to formaldehyde production process online optimization.Results show that ,the method is simple and easy to implement,robust in versatility,and it has high accuracy and reliability,so it is effective for chemical process optimization.
【Key words】 chaos optimization; exact penalty function; soft sensing; formaldehyde production process;
- 【文献出处】 化工自动化及仪表 ,CONTROL AND INSTRUMENTS IN CHEMICAL INDUSTRY , 编辑部邮箱 ,2000年02期
- 【分类号】TP18
- 【被引频次】22
- 【下载频次】161