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飞灰含碳量是衡量电站锅炉燃烧效率的重要参数,飞灰含碳量的准确测量有助于调整锅炉燃烧。本文采用了狼群神经网络算法,利用狼群算法对神经网络进行优化,将优化过后的神经网络用于飞灰含碳量的预测,并分析了经过狼群神经算法与遗传神经网络的预测效果。
The carbon content of fly ash is an important parameter to measure the combustion efficiency of power plant boilers. The accurate measurement of carbon content in fly ash helps to adjust the boiler combustion. In this paper, wolf neural network algorithm is used, the wolf group algorithm is used to optimize the neural network, the optimized neural network is used to predict the carbon content of fly ash, and the prediction effect of wolf group neural network and genetic neural network .