基于组合熵值马尔科夫模型的住宅用地价格预测研究

Investigating the price forecast of residential land based on a combined entropy Markov model

住宅用地地价是城市房地产价格发展的基础。本文通过建立灰色GM(1,1)模型和无偏灰色GM(1,1)模型,并利用熵值法建立组合预测模型的方法,对杭州市住宅用地地价进行组合预测。同时选用马尔科夫链模型对熵值法组合模型预测结果进行修正处理,以进一步提高预测结果的可信度。实例表明,熵值法组合预测模型与单一预测模型相比,实用性更强,预测精度也得到有效提高。

The price of residential land is the foundation of urban real estate price development. This paper establishes the grey GM (1,1) model and the unbiased grey GM (1,1) model, and establishes combination forecasting model by using the entropy method to forecast the residential land prices of Hangzhou. We show that the combination forecasting model of entropy value method is more practical than the single prediction model, and the prediction accuracy improves. With the Markov chain model, the prediction results of entropy value method combination model are modified, and improve the reliability of the prediction results.