遗传算法及神经网络在锅炉负荷优化分配中的应用
Application of Genetic Algorithm and Neural Network in the Optimization of Boiler Load Assignment
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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.Abstract: 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.
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