Abstract
With the rapid development of society, the real estate economy, as an important part of Chinese economy, is showing a growing trend. But it is also the most likely to generate bubble economy, causing financial risks; it will trigger a series of social contradictions and cause social unrest in severe cases. Therefore, it is urgent to improve and optimize the real estate evaluation model. In this study, the real estate was evaluated based on the neural network model optimized by genetic algorithm. Through sorting out and summarizing the real estate data in a period of time, the corresponding model was established and the test data were obtained. The average relative error value of the genetic algorithm optimized neural network model was 3.552, which was smaller than that of the Back-Propagation (BP) neural network prediction model. The experimental conclusion that the new network model was better than the traditional model was obtained. This work opens up a new route of real estate evaluation.
Highlights
With the acceleration of urbanization, the real estate industry is developing vigorously and irresistibly
Under the same number of training, the mean square error of the optimal BP neural network obtained by the genetic neural network model was smaller than that obtained by the BP neural network model
The problem of real estate evaluation was studied, and a real estate evaluation model based on genetic algorithm optimized neural network was put forward
Summary
With the acceleration of urbanization, the real estate industry is developing vigorously and irresistibly. An innovative and unified evaluation method based on the traditional mass assessment technology was proposed to deeply study the characteristics of the real estate market in China. Zhang and Ji (2010) put forward a method based on Back-Propagation (BP) neural network theory to analyze the real estate investment risk and its changing law, which improved the accuracy of evaluation and was conducive to risk avoidance. The simulation experiment of the real estate evaluation model based on genetic algorithm optimized neural network was carried out to effectively improve and optimize the real estate evaluation model. The accuracy and practicability of the method was tested, which is conducive to promoting the healthy development of the real estate industry. Sun: Real Estate Evaluation Model Based on Genetic Algorithm Optimized Neural Network
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