计算机与数字工程2019，Vol.47Issue(12)：3209-3213,5.DOI:10. 3969/j. issn. 1672-9722. 2019. 12. 051
基于改进支持向量机的工程造价预测模型
Engineering Cost Prediction Model Based on Improved Support Vector Machine
摘要
Abstract
The prediction of project cost is a hot topic in the field of engineering management. In view of the low prediction ac?curacy and low modeling efficiency of current engineering cost prediction model,a prediction model of engineering cost based on im?proved support vector machine is proposed. The first collection of historical data and the project cost,they must be preprocessed, and then the improved least squares support vector machine is used to the project cost modeling of training samples,and by using particle swarm algorithm,the parameters of the model are determined,so as to establish a prediction model of project cost,finally it is realized by the comparative experiments,simulation in project cost prediction Matlab toolbox of 2014R. The results show that the improved support vector machine greatly improves the accuracy of prediction of engineering cost,engineering cost and overall pre?diction performance are significantly better than the contrast model,which has higher practical value.关键词
工程造价/预测模型/改进支持向量机/粒子群优化算法Key words
engineering cost/prediction model/improved support vector machine/particle swarm optimization algorithm分类
交通工程引用本文复制引用
朱琳,刘春..基于改进支持向量机的工程造价预测模型[J].计算机与数字工程,2019,47(12):3209-3213,5.基金项目
四川建筑职业技术学院2015年院级科研项目"建筑工程造价的非线性建模与预测研究"(编号:2015KJ07)资助. （编号:2015KJ07）
