中国电力2017，Vol.50Issue(3)：168-173,6.DOI:10.11930/j.issn.1004-9649.2017.03.168.06
基于改进萤火虫算法优化SVM的变电工程造价预测
Substation Engineering Cost Forecasting Method Based on Modified Firefly Algorithm and Support Vector Machine
摘要
Abstract
The cost level of substation engineering is closely related to the integrated economy of power grid projects,and the cost level forecasting is a crucial tool for controlling cost and improving cost rationality.Based on the conventional firefly algorithm,the Gaussian Disturbance is introduced into the firefly algorithm to improve the update equation,which aims to improve the searching ability and optimize the SVM parameters.By operating the Schaffer testing function,it is discovered that the Gaussian disturbance firefly algorithm has better convergence rate and searching abihty.The case study of substation engineering in Guangdong Province further proves that the proposed model has higher forecasting accuracy and effectiveness关键词
萤火虫算法/支持向量机/高斯扰动/变电工程/造价预测Key words
firefly algorithm/support vector machine/Gaussian disturbance/substation engineering/cost forecasting分类
信息技术与安全科学引用本文复制引用
宋宗耘,牛东晓,肖鑫利,朱琳..基于改进萤火虫算法优化SVM的变电工程造价预测[J].中国电力,2017,50(3):168-173,6.基金项目
国家自然科学基金资助项目(71471059) （71471059）
中央高校基本科研业务费专项资金资助项目(2016XS75 （）
2016XS73) （）
This work is supported by National Natural Science Foundation of China Project (No.71471059) （No.71471059）
Fundamental Research Funds for the Central Universities (No.2016XS75 （）
No.2016XS73). （）
