Research On Prediction Model Of Municipal Solid Waste Transportation Based On Elman Neural Network

With the accelerating of urbanization,urban economy fast development,municipal solid waste yields rapidly growing at an annual rate of 3% ~ 10%.The current some garbage disposal infrastructure cannot meet the needs of rapid economic development,will lead to many cities surrounded by rubbish.Since the long,not only will cause serious environmental pollution,hinder the growth of the economy,more will have been threatened by the body of any resident.According to the above problem,this paper on the basis of our country historical municipal solid waste yields,using grey correlation filtering the main factors influencing the change of municipal solid waste yields.In this paper based on BP neural network and Elman neural network predictive model of municipal solid waste yields.Respectively with two kinds of models to forecast the municipal solid waste yields,through to the higher prediction accuracy test sample selection of Elman neural network model to predict the next few years in our country municipal solid waste yields.municipal solid waste yields as city one of the people's livelihood problem that nots allow to ignore,predict the municipal solid waste yields is significant.It provide a basis for waste comprehensive treatment,effective control of garbage growth,reduce environmental pollution.For the urban construction planning and environmental health planning to provide decision-making information,has an important influence to refuse transfer station layout.In wuhan,for example,in 2004-2014 in wuhan municipal solid waste yields and 11 influence factors of the data,using the grey correlation method to screen the six main factors influencing trash municipal solid waste yields most relevant.Contrast analysis was carried out on the built prediction model,through the calculation model and the actual and estimated values of the average absolute percentage error and coefficient equal to verify prediction precision of the model,the results show that the accuracy of Elman neural network forecasting model is superior to the BP neural network prediction model.And by using the model of the 2015-2018 in wuhan municipal solid waste yields forecast,forecast the municipal solid waste yields were 285.28(ten thousand tons),287.83(ten thousand tons),304.98(ten thousand tons),291.42(ten thousand tons).Research results show that based on grey correlation and prediction model of municipal solid waste yields Elman neural network can effectively predict municipal solid waste yields,has good feasibility and applicability.