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Construction of Air Quality Evaluation System Based on FCM Algorithm and BP Neural Network.

         

摘要

cqvip:In order to solve the limitations of existing air quality evaluation system,a new air quality evaluation system was established based on FCM,the BP neural network,with the aim to provide scientific bases for the targeted and efficient control of air pollution,formulation of prevention and control strategy,and improvement of living environment. Based on the existing data of 6 air quality indices,the air quality data were reclassified by using FCM algorithm,obtaining the clustering center,which minimized the cost function of non-similar index. Then,the reclassified 6 classes of data were proceeded with BP neural network training and simulation,so as to achieve the purpose of identification,thereby forming a new air quality evaluation system.

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