基于大数据的电力物资信息价预测模型研究  

Research on Information Price Prediction Model of Electric Power Materials Based on Big Data

作　　者：胡志红 王语涵 郑桢 杨鹏绪 陈世坤 HU Zhi-hong;WANG Yu-han;ZHENG Zhen;YANG Peng-xu;CHEN Shi-kun(Hainan Power Grid Co.,Ltd.,Materials Department,Haikou 570203 China;Kunming Nengxun Technology Co.,Ltd.,Kunming 650000 China)

机构地区：[1]海南电网有限责任公司物资部,海南海口570203 [2]昆明能讯科技有限责任公司,云南昆明650000

出　　处：《自动化技术与应用》2020年第12期44-46,55,共4页Techniques of Automation and Applications

摘　　要：本文基于蝙蝠算法-支持向量机预测模型与变异系数统计模型,设计大数据视域下电力物资信息价预测流程。首先详细分析预测模型与统计模型,其次设计预测方法具体流程,再次进行电力物资信息价预测模型详细设计,最后以大数据为载体优化信息价预测模型。基于蝙蝠算法不仅可显著提升支持向量机预测精确度,还可通过引进价格影响因素预测信息价,以此保证信息价预测准确性与可靠性,切实解决大数据统计信息价的不足,表明此预测流程模型的适用性良好,值得大力推广与应用。In this paper,based on bat algorithm-support vector machine prediction model and coefficient of variation statistical model,the prediction process of power material information price under big dataundefineds visual field is designed.First of all,the prediction model and statistical model are analyzed in detail,secondly,the specific flow of prediction method is designed,and then the detailed design of power material information price prediction process is carried out.Finally,big data is used as the carrier to optimize the information price prediction model.The bat algorithm can not only significantly improve the prediction accuracy of support vector machine,but also ensure the accuracy and reliability of information price prediction by introducing price influencing factors to ensure the accuracy and reliability of information price prediction,and effectively solve the shortcomings of big dataundefineds statistical information price.It shows that the prediction process model has good applicability and is worth popularizing and applying.

关 键 词：大数据 蝙蝠算法 电力物资 信息价 预测模型 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]