基于MCS-SVM的建筑工程造价建模与预测  

Project Cost Modeling and Forecasting Based on MCS-SVM

作　　者：刘春[1] 

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：《微型电脑应用》2017年第10期39-42,共4页Microcomputer Applications

基　　金：四川建筑职业技术学院2015年院级科研项目(2015KJ07)阶段性研究成果之一

摘　　要：工程造价的建模与预测对工程管理具有十分重要的研究意义,为了提高工程造价预测准确性,针对当前工程造价预测模型的局限性,设计了改进布谷鸟搜索算法优化支持向量机的工程造价预测模型(MSC-SVM)。对当前工程造价预测建模的现状进行分析,指出当前存在的主要问题,引入支持向量机建立工程造价预测模型,并通过改进布谷鸟搜索算法估计支持向量机参数,采用具体工程造价数据对模型性能进行分析。测试结果表明,提出的模型获得了较可靠的工程造价预测结果,可以为工程管理决策提供有价值的参考信息。Project cost modeling and forecasting have very important research significance to the project management. In order to improve the accuracy of project cost forecasting, in view of the limitation of current project cost forecasting models, a novel method for project cost modeling and forecasting is proposed based on MCS-SVM. First of all, the status of current project cost forecasting modeling is analyzed, and main problems are pointed out. Secondly, support vector machine （SVM） is introduced to establish the model of project cost forecasting, Cuckoo search algorithm is used to estimate the support vector machine parameters. At last, a specific project cost data are selected to analyze the model performance. The test results show that the proposed model can get reliable prediction of project cost, it can provide valuable reference information for project management and decision-making.

关 键 词：工程管理 造价建模 布谷鸟搜索算法 支持向量机参数 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]