Real Estate Price Evaluation System Based on BP Neural Network Algorithm

With the increasing emphasis and investment in the real estate industry, the real estate appraisal business has also become an important part of the real estate business and has developed rapidly. However, there are theoretical problems in the current real estate appraisal, ineffective appraisal work, and incorrect estimation methods, all of which are affecting the progress of the real estate appraisal business. Therefore, in-depth research on valuation theory and valuation methods has theoretical significance and value. The purpose of this paper is to study the real estate price evaluation system based on BP neural network algorithm. On the basis of analyzing the commonly used real estate evaluation methods, the BP neural network model is established, and the real estate price evaluation system based on the BP neural network model is designed and implemented. Finally, this paper takes the real estate of a certain tier city as a sample, and imports it into the neural network for training. Through calculation, it is found that the real estate value can be evaluated more accurately and quickly through BP neural network calculation.