摘要
针对并列运行锅炉群的负荷优化分配问题,提出用遗传神经网络辨识给煤量-产气量模型,并用改进的遗传算法进行负荷优化分配.给出了改进遗传算法和遗传神经网络的辨识原理.负荷优化分配结果表明,该方法优于平均分配方法.
Optimization problem of in the assignment boiler loading when in parallel operation is aimed at. Genetic neural network is used to identify the coal supply and steam production model and improved genetic algorithm is applied to optimize assignment. The advantages of the improved genetic algorithm and the identification theory of the genetic neural network are described. The results of optimized assignment of load is shown to be better than that of the average assignment method.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2005年第11期944-948,共5页
Transactions of Beijing Institute of Technology
基金
北京市共建重点实验室资助项目(SYS100070417)
关键词
锅炉
负荷分配
遗传算法
神经网络
优化分配
boiler
load assignment
genetic algorithm
neural network
optimization
