Determination of Real Estate Price Based on Principal Component Analysis and Artificial Neural Networks
Real estate industry is both capital-intensive, highly related industries and industries essential to provide the daily necessities.However,the real estate pricing models and methods of research rarely receive the critical attention and development it deserves.This paper utilizes the principal components analysis method of multi-dimensional statistical analysis and artificial neural networks to determine the price of real estate.By using principal component method to process a number of listed real estate pricing indices.Firstly, the index system of accident risk was established.Then principal component analysis was applied to eliminate the indexes having the relativities and overlap information. Finally, based on historical data and artificial neural networks, a new real estate pricing models was established. The experiment results show that this method is effective and precise.
principal component analysis(PCA) artificial neural networks real estate price determination
Huawang Shi
School of Civil Engineering Hebei University of Engineering Handan, P.R.China
国际会议
长沙
英文
314-317
2009-10-10（万方平台首次上网日期，不代表论文的发表时间）