微型机与应用2017，Vol.36Issue(9)：60-63,66,5.DOI:10.19358/j.issn.1674-7720.2017.09.018
基于遗传算法的BP神经网络优化动力配煤模型的研究
The BP neural network based on genetic algorithm optimization model of power coal blending
李吉朝 1张海英 1王惠琴2
作者信息
- 1. 西安理工大学 复杂系统控制与智能信息处理重点实验室,陕西 西安 710048
- 2. 西安市环境监测站,陕西 西安 710048
- 折叠
摘要
Abstract
The BP neural network has strong learning ability, but in the traditional studies,hidden layer nodes, learning factors and momentum factors tend to use trial and error method to get relatively better value,at the same time, trial and error method in a waste of more time,the BP neural network output may not be ideal,this caused some difficulties to research.In this paper, the intelligent algorithm is applied to solve the problem of the BP neural network optimization.Genetic algorithm as a kind of random search algorithm,it can find the global optimal solution quickly, can be applied to the optimization problem.This paper uses genetic algorithm to optimize the BP neural network parameters,and applies the improved BP neural network in the study of nonlinear model of power coal blending.The results show that using genetic algorithm to optimize the BP neural network has strong ability of prediction,calorific value of coal quality prediction error is superior to the average linear model,and the simulation results show the approximate linear dynamic coal blending model of nonlinear model,the output value of the BP network error is less volatile,the result is ideal.关键词
动力配煤/BP神经网络/遗传算法/非线性Key words
power coal blending/BP neural network/genetic algorithm/nonlinear分类
计算机与自动化引用本文复制引用
李吉朝,张海英,王惠琴..基于遗传算法的BP神经网络优化动力配煤模型的研究[J].微型机与应用,2017,36(9):60-63,66,5.
