Application Of BP Neural Network In The Real Estate Tax Base Mass Appraisal

Chinese current property tax is based on The Interim Regulations on property tax,1986. The main object of taxation is the production and operation of enterprises and personal property for rent. The resident’s property for living or investment is free of duty. But in recent years because of the real estate market continues to improve, making a large number of investment into the real estate market, resulting in real estate market bubble. Real estate prices gradually rise but the housing vacancy rate is high. The State Council decided to retain tax on resident’s the real estate in a few years. On the one hand, it can stabilize the real estate market, on the other hand it can also expand the local government revenue sources. Real estate tax levy should periodically assess the value of real estate, Therefore, the mass appraisal is the best solution to solve this problem.Based on reading a large number of domestic and foreign literature, my paper firstly introduces the connection and difference between the existing tax assessment and real estate appraisal and believe that market method, cost method and income method of traditional valuating can’t meet the assessment requirements. Therefore we must be used the mass appraisal as the tax base valuation method. We analyzed the mass appraisal ’s characteristics, advantages and the premise of using. Then analyze the the feasibility of BP neural network is used in mass appraisal, and analyzes the application of neural network method in the evaluation of the tax base to the policy and technical support. At present. The research in this field is lack of the process design for the mass appraisal so in this paper design the process for BP neural network applied to the tax base assessment. Finally, taking ChaoYang District, Beijing as the research object, to verify that the BP neural network method for tax assessment is effective and accurate for evaluation of a large number of real estate value. This paper provides a reference for future similar tax base assessment.