| 基于BP神经网络的河南开封市住房需求预测 |
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| 引用本文： | 范振东.基于BP神经网络的河南开封市住房需求预测[J].科技广场,2010(3):21-23. |
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| 作者姓名： | 范振东 |
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| 作者单位： | 东华理工大学地球科学与测绘工程学院,江西,抚州,344000;开封电子科技学校,河南,开封,475100 |
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| 摘 要： | 影响住房需求的因素众多,错综复杂,并且具有非线性的特征。本文通过对住房需求影响因素的分析,用BP神网络来购建住房的需求模型。根据河南开封市的有关统计数据,用BP神经网络优化算法进行住房需求预测,并与多元回归测方法进行对比。结果表明,BP神经网络具有较好的适应性和较高的预测精度。
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| 关 键 词： | BP神经网络 开封市 住房需求预测 |
Housing Needs Forecast Based on BP Neural Network in Kaifeng City in Henan Province |
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| Fan Zhendong.Housing Needs Forecast Based on BP Neural Network in Kaifeng City in Henan Province[J].Science Mosaic,2010(3):21-23. |
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| Authors: | Fan Zhendong |
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| Institution: | 1.Institute of Earth Sciences and Mapping/a>;East China University of Technology/a>;Jiangxi Fuzhou 344000/a>;2.Kaifeng Electron Science and Technology School/a>;Henan Kaifeng 475100 |
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| Abstract: | Many factors affect housing demand,Which is complex and has nonlinear characteristics.In this paper,BP neural network was used to build a housing demand model based on the analysis of housing needs factors.According to relevant statistical data Kaifeng City in Henan,Using BP neural network optimization algorithms forecast housing demand,and compared with the demand of multivariate regression method.The results showed that BP neural network had better adaptability and higher prediction accuracy. |
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| Keywords: | BP Neural Network Kaifeng City Housing Demand Forecast |
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