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基于遗传算法优化BP神经网络的锅炉燃烧建模

2009-03-27

:针对传统BP神经网络存在着容易陷入局部极小点、训练时间长等缺点,本文利用遗传算法对BP神经网络进行优化,将其用于锅炉燃烧系统的建模中。结果表明:本文的模型比文献8中单用BP神经网络建立的模型精度更高,故可行性好,对电厂燃烧的模拟与运行的经济性有帮助。

Boiler Combustion Modeling of BP Neural Network Based on Genetic Algorithm Optimization

Cao Hong-fei

(School of Power and Engineering, Nanjing Normal University, Nanjing 210042, China)

Abstract: In order to solve the problems in traditional BP neural networksuch as local minimal point and over long time training, a method of BP neural network based on genetic algorithm optimization is used to obtain a model of boiler combustion in this paper. And the method is proved to be feasible and helpful for combustion modeling and economical running by the comparison with the result in reference 8.

Keywords: boiler; combustion modeling; genetic algorithm; BP neural network