Study On Carbon Effect Assessment Of County Town Planning Land Use Based On BP Neural Network:

Low-carbon development has become a global consensus.Integrating planning scheme carbon emission quantification technology into existing planning preparation processes and systems is an important direction for planning technological innovation in the context of low-carbon urban construction.Aiming at the problem of carbon emission forecasting of current planning schemes,based on the perspective of planning land use,and referring to the method of building energy consumption prediction,the BP neural algorithm using artificial intelligence method is used to predict the carbon effect of the planning scheme.Based on the measured data obtained from the large sample survey.The main contents of the main research are as follows:Firstly,the existing researches are summarized and summarized from three aspects: the relationship between land use and carbon effect,the spatial coupling relationship of carbon emissions from land use,and the successful evaluation of carbon effects in domestic and international planning schemes;The characteristics of carbon effect assessment proposed the mechanism and method path of carbon effect assessment in this study,and clarified the use of above-ground building energy consumption as the main accounting content,and then analyzed the existing energy consumption prediction technology,and chose BP of machine learning method.As the core technology method for predicting land carbon emission in this study,the neural algorithm establishes the evaluation operation process of the carbon effect of the planned land use plan.Finally,taking Changxing County as an example,the case study of establishing the method and the large sample survey obtained through the investigation The data is a model training sample,through the following steps:variable selection,sample data acquisition and calculation,data and processing,training samples and prediction of these operational processes;the sample data test results show that the model error is about 7%,indicating The evaluation method using this model has certain in the actual evaluation.Accuracy and operability.Finally,this method has been applied practically through the planning and land use plan of Zhongxing and micro level in Changxing County.The results of case study show that the method of estimating the carbon effect of planning land based on BP neural network is a suitable method for assessing the carbon effect of urban planning land in county,which has strong feasibility.