Evaluation Of Real Estate Tax Base Batch Based On BP Neural Network

With the continuous development of China's real estate market and the continuous promotion of fiscal and tax system reform,tax base evaluation,as one of the important supporting measures of real estate tax management reform,is conducive to regulating the tax behavior of real estate developers,ensuring tax compliance,and improving tax credibility.In addition,as the ballast and stabilizer of China's economy,the development of the real estate market and China's economic development come down in one continuous line.In the fourteenth five year plan and the long-term goal of 2035,it is clearly proposed to "improve the linkage mechanism between house price and land price","promote the legislation of real estate tax,and improve the local tax system".Therefore,the real estate market will continue to develop,and the research on the real estate market will continue to become an upsurge.In order to promote the legislation of real estate tax,the healthy development and fair trade of real estate cannot do without the evaluation of tax base of real estate tax.As a complex system engineering,real estate tax base evaluation needs to evaluate a large number of properties.The basic data are complex and diverse,and the fairness and efficiency of tax base evaluation should also be considered.However,at present,China's real estate tax base evaluation is mainly based on market method,cost method and income method,but this method also has many problems,such as time-consuming It's long and costly.Compared with these three methods,batch evaluation uses big data and computer intelligence to solve the problem of single case evaluation,and the error between the evaluation results and the actual transaction price is very small,so batch evaluation can be applied in China's real estate tax base evaluation and widely implemented.In addition,after years of research and practice,a relatively mature real estate tax base evaluation system has been formed in the world,with the main purpose of tax assessment in retention link and the core of mass assessment.In this paper,through reading the literature of real estate tax base batch evaluation at home and abroad,we learn from the previous methods and experience.Firstly,this paper discusses the theoretical achievements of domestic and foreign scholars in tax base evaluation,and puts forward the author's own research methods and framework.Secondly,it also summarizes the basic theoretical knowledge involved in real estate tax base batch evaluation,such as the concept and principle of real estate tax base evaluation,compares the advantages and disadvantages of various methods and technologies,and lays the foundation for this paper to use BP neural network.BP neural network has the advantages of fault tolerance,fast calculation speed,self-organization,self-learning and self adaptation,as well as fitting any non-linear relationship.This paper also lists the factors that affect the real estate market,taking this as the starting point to quantify the real estate tax base evaluation index.Finally,this paper takes the real estate price of second-hand houses in Hohhot as the research object,which is mainly because some families have limited ability to pay for commercial houses,and more and more families choose to buy second-hand houses,so the data of second-hand houses are easy to obtain In addition,through the setting of input layer,hidden layer and output layer,the empirical model analysis is carried out,and the results of the model are verified.It is found that the difference between the error and the actual transaction price is very small,which proves the accuracy and rationality of BP neural network in real estate tax base batch evaluation.