基于改进GM模型的房价预测模型

The Housing Price Forecasting Model Based on Improved GM Model

摘要: 本文将以青岛西海岸新区商品房价格为例，针对商品房价格呈现动态变化的特点，利用改进的GM (1, 1)模型与马尔可夫模型结合，提出一种基于时间序列的预测模型，对青岛西海岸新区的商品房价格进行预测。根据灰色GM (1, 1)模型适合对数据量较少、波动不大的短期数据进行预测，而马尔可夫模型适用于数据波动较大的预测过程的特点，通过结合改进的GM (1, 1)模型与马尔可夫模型的优点，建立房价指数的预测模型。实验结果表明，该模型的拟合精度较高，是一种较为可行的房价预测模型。

Abstract: In view of the dynamic changes characteristics of real estate price, this article takes the real estate price of The West Coast New Area of Qingdao as an example, combines the improved grey GM (1, 1) forecast model with Markov model, and puts forward a new time series basing forecast model to forecast the real estate price of The West Coast New Area of Qingdao. The grey GM (1, 1) model is suitable for short-term data forecasting with fewer data and fewer fluctuations, while the Markov model is suitable for prediction processes with large data fluctuations. By combining the advantages of the improved GM (1, 1) model with the Markov model, a new forecast model is established for real estate price forecasting. The experimental results show that the accuracy of this model is high, and it is a feasible model for house price forecasting.