| 基于网格寻优SVR房价预测模型——以郑州市为例 |
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| 引用本文： | 张彦周,贾利新. 基于网格寻优SVR房价预测模型——以郑州市为例[J]. 河南科学, 2014, 0(8): 1659-1663 |
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| 作者姓名： | 张彦周 贾利新 |
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| 作者单位： | 1. 河南职业技术学院基础教学部,郑州,450046
2. 信息工程大学理学院,郑州,450001 |
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| 基金项目： | 国家自然科学基金(U1304610);河南省科技厅重大科技攻关课题 |
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| 摘 要： | 分析了影响房价的因素,利用房价滞后性的特点,将某年的经济指标与下一年的房价对应.利用回归支持向量机对房价进行学习、预测,同时采用网格寻优算法计算最优的学习参数.最后以郑州市的房地产数据进行仿真实验,取得了较为理想的效果.
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| 关 键 词： | 回归支持向量机 房价预测 网格参数寻优 |
SVR Housing Forecast Model Based on Grid Optimization--Zhengzhou City as an Example |
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| Zhang Yanzhou,Jia Lixin. SVR Housing Forecast Model Based on Grid Optimization--Zhengzhou City as an Example[J]. Henan Science, 2014, 0(8): 1659-1663 |
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| Authors: | Zhang Yanzhou Jia Lixin |
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| Affiliation: | Zhang Yanzhou, Jia Lixin (1. Basic Courses Department, Henan Polytechnic College, Zhengzhou 450046, China： 2. Institute of Sciences, Information Engineering University, Zhengzhou 450001, China) |
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| Abstract: | We analyzed the factors that affect housing prices, advantage of the characteristics of hysteresis of housing prices, then, maked learning samples corresponding between the economic factors of one year and the housing prices of the next year. The regression support vector machine （SVR） was used for houing prices learning and prediction. Furthermore grid optimization algorithm was adopted for calculating optimal parameters of learning. Finally, we carried out a simulative predution with relevant data of Zhengzhou real estate and achieved good results. |
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| Keywords: | SVR housing prices prediction the optimal parameters by grid search method |
| 本文献已被 CNKI 维普 等数据库收录！ |
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