地统计学与支持向量机相融合的建筑工程造价预测  

Prediction of Construction Cost Based on Integration of Geostatistics and Support Vector Machines

作　　者：刘春[1] LIU Chun(Network Management Center, Sichuan College of Architectural Technology, Deyang 618000, Chin)

机构地区：[1]四川建筑职业技术学院网络管理中心,德阳618000

出　　处：《计算机系统应用》2018年第4期272-275,共4页Computer Systems & Applications

基　　金：四川建筑职业技术学院2015年院级科研项目(2015KJ07)

摘　　要：为了精确对建筑工程造价进行预测,根据建筑工程造价数据间的时间相关性和非线性变化特点,构建了地统计学与支持向量机相融合的建筑工程造价预测模型.首先收集建筑工程造价数据,然后根据建筑工程造价数据的时间相关性,采用地统计学估计时间序列的嵌入维数,构建建筑工程造价的学习样本,最后通过支持向量机建立工程造价预测模型,并通过实例对性能进行测试与分析.结果表明,本文模型可以有效拟合建筑工程造价数据时间相关性,获得高精度的建筑工程造价预测结果,而且结果要明显优于其它模型.In order to accurately predict the cost of construction project, according to the sample time dependent and nonlinear characteristics, this study has constructed a prediction model of construction project cost based on the geostatistics and support vector machine. Firstly, the cost data of construction engineering are collected, and then, the embedding dimension of time series is obtained by geostatistics according to time correlation of construction cost sample, and the construction cost learning samples of construction project, support vector machine is used to establish project cost prediction model, and test and analysis of the performance through the prediction example. The results show that the proposed model can effectively fit the construction cost of sample time correlation, and get higher accuracy of construction cost prediction, and the result is much better than the other models.

关 键 词：建筑工程造价 嵌入维数 地统计学 时间相关性 支持向量机 

分 类 号：TU723.3[建筑科学—建筑技术科学]