计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (35): 223-225.DOI: 10.3778/j.issn.1002-8331.2008.35.067

• 工程与应用 • 上一篇    下一篇

支持向量机在天然气企业产量预测中的应用

赵相东1,张 浩1,2,嵇 晓3,张 辉1   

  1. 1.同济大学 CIMS研究中心,上海 200092
    2.上海电力学院 电力与自动化工程学院,上海 200090
    3.上海宝信软件股份有限公司,上海 200092
  • 收稿日期:2007-12-20 修回日期:2008-03-14 出版日期:2008-12-11 发布日期:2008-12-11
  • 通讯作者: 赵相东

Application of Support Vector Machine in production forecast in natural gas enterprise

ZHAO Xiang-dong1,ZHANG Hao1,2,JI Xiao3,ZHANG Hui1   

  1. 1.CIMS Research Center,Tongji University,Shanghai 200092,China
    2.School of Electric Power and Automation Engineering,Shanghai University of Electric Power,Shanghai 200090,China
    3.Shanghai Baositht Software Co.,Ltd.,Shanghai 200092,China
  • Received:2007-12-20 Revised:2008-03-14 Online:2008-12-11 Published:2008-12-11
  • Contact: ZHAO Xiang-dong

摘要: 天然气企业副产品产量受市场的波动影响很大,对于副产品产量的预测,通常都是依靠工作人员的经验,工作量大,效率不高。回归统计分析方法及传统的机器学习方法在这个领域的应用存在着一些局限性,介绍一种新的机器学习算法—支持向量机,以企业为背景,运用支持向量机算法来解决预测问题,实验证明采用支持向量机能够满足企业的需求,得到满意的效果。

关键词: 支持向量机, 统计学习理论, 主成分分析, 产量预测

Abstract: The production of the byproduct in natural gas enterprise is greatly affected by the market vibration,the forecast of the byproduct production usually relies on the experience of the people concerned.The amount of work is large,but the efficiency is relatively low.The statistical analysis method and the traditional machine learning method have some limitations in the application in this field.So a new machine learning method—Support Vector Machine,in the background of the enterprise is introduced.It can solve the forecast problem by means of Support Vector Machine method.It is proved that by using the support vector machine,the enterprise’s meet can be met,and it can also produce satisfactory result.

Key words: Support Vector Machine(SVM), statistical learning theory, Principal Components Analysis(PCA), forecast of production