Abstract

<p>With the rapid development of computer, artificial intelligence and big data technology, artificial neural networks have become one of the most powerful machine learning algorithms. In the practice, most of the applications of artificial neural networks use back propagation neural network and its variation. Besides the back propagation neural network, various neural networks have been developing in order to improve the performance of standard models. Though neural networks are well known method in the research of real estate, there is enormous space for future research in order to enhance their function. Some scholars combine genetic algorithm, geospatial information, support vector machine model, particle swarm optimization with artificial neural networks to appraise the real estate, which is helpful for the existing appraisal technology. The mass appraisal of real estate in this paper includes the real estate valuation in the transaction and the tax base valuation in the real estate holding. In this study we focus on the theoretical development of artificial neural networks and mass appraisal of real estate, artificial neural networks model evolution and algorithm improvement, artificial neural networks practice and application, and review the existing literature about artificial neural networks and mass appraisal of real estate. Finally, we provide some suggestions for the mass appraisal of China's real estate.</p>

Highlights

  • China appraisal industry was started in the late 1980s, after nearly three decades of development, appraisal industry has grown rapidly

  • This article defines the concept of mass appraisal of real estate and reviews the evaluation from artificial neural network and real estate tax base valuation theory, artificial neural networks model evolution and algorithm improvement, artificial neural networks practice and application, in the end provide some useful suggestions for the mass appraisal of China's real estate

  • The second is the evolution of the artificial neural networks models and the improvement of the computer algorithms

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Summary

Introduction

China appraisal industry was started in the late 1980s, after nearly three decades of development, appraisal industry has grown rapidly. In 2016, the People's Republic of China Appraisal Law was formally promulgated, setting the legal status of the appraisal industry for the first time. Artificial neural networks is a very popular algorithm in machine learning field in the 1980s, but declined in the mid-1990s. With the "deep learning" trend, artificial neural networks become one of the most powerful machine learning algorithms. There is a big gap between our appraisal of the level of industrialization information construction and development needs. This article defines the concept of mass appraisal of real estate and reviews the evaluation from artificial neural network and real estate tax base valuation theory, artificial neural networks model evolution and algorithm improvement, artificial neural networks practice and application, in the end provide some useful suggestions for the mass appraisal of China's real estate

The mass appraisal of real estate
Artificial neural networks and back propagation neural network
Artificial neural networks and mass appraisal theory
Artificial neural networks model evolution and algorithm improvement
Domestic real estate tax base valuation theory
Domestic mass appraisal of practical applications
Domestic artificial neural networks application and model evolution
Conclusions and future prospects
Authors
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