摘要
保障性住房建设问题是影响人民的重大民生问题,我国近年来对保障性住房建设问题给予了很大的关注。但保障性住房仍存在着覆盖水平低、供需缺口大等问题,研究该课题的关键在于如何准确地预测保障性住房需求量。本文以河北省为例,利用蛙跳算法建立组合优化模型,对未来保障性住房的需求量进行预测,并与GM(1,1)模型和SVM模型作对比。结果表明,本文建立的模型发挥了组合优化预测模型的优点,降低了随机因素的影响,提高了保障性住房需求量预测的精度,所得的预测结果更为理想,对推动保障性住房的可持续发展具有重要意义。
The situation of the affordable housing construction is a significant issue in people＇s life. In recent years, the affordable housing construction in our country has been given a great concern. But there are still many problems of the affordable housing, such as the low cover degree and the big gap between supply and demand. The key point to solve this problem is to predict the demand of the affordable housing accurately. In this paper, the demand of the affordable housing in Hebei province is forecasted by constructing the portfolio optimization model with leapfrog algorithm, compared with the single GM （1,1） model and SVM model. The result shows that the portfolio optimization model makes use of the advantages of the portfolio optimization forecasting model, reduces the influence of random factors, improves the accuracy of forecasting the demand of affordable housing, and obtains more desirable prediction result, which is important in improving the sustainable development of affordable housing.
出处
《企业经济》
北大核心
2015年第8期146-150,共5页
Enterprise Economy
基金
国家社会科学基金项目"符合中国国情的住房保障和供应体系研究"(批准号:14BJY060)
河北省社会科学基金项目"河北省保障性住房可持续发展研究"(批准号:HB14GL028)
