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基于混沌v-支持矢量机的产品销售预测模型
  • 期刊名称：机械工程学报
  • 时间：0
  • 页码：128-135
  • 语言：中文
  • 分类：TP391[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术] TH12[机械工程—机械设计及理论]
  • 作者机构：[1]东南大学复杂工程系统测量与控制教育部重点实验室,南京210096, [2]东南大学江苏省微纳生物医疗器械设计与制造重点实验室,南京211189
  • 相关基金：国家高技术研究发展计划（863计划,2007AA042112）、国家自然科学基金（50875046,60904043）、中国博士后科学基金（20090451152）和江苏省博士后科研资助计划（0901023c）和东南大学博士后重点科研A类资助项目.
  • 相关项目：制造系统成品需求短期预测模型研究及应用
作者： 吴奇|严洪森|
关键词： 混沌, 支持矢量机, 遗传算法, 销售预测, Chaos Support vector machine Genetic algorithm Sale forecasting
中文摘要：

针对制造企业产品销售时序具有多维、小样本、非线性和多峰等特征，将混沌理论与支持矢量机（Support vector machine．SVM）参数优选方法相结合，证明了结构风险最小化原则是在概率意义下近似正确的，由此得到支持矢量机的表现形式并不是唯一的，具有多样性的特征，在此基础上提出一种混沌v-支持矢量机（Chaotic-v SVM，Cv-SVM）模型，给出相应的产品销售预测方法。最后进行了汽车销售时序预测，结果表明基于Cv-SVM的产品预测方法是有效和可行的。

英文摘要：

Aiming at the product sale time series of manufacturing enterprise with multi-dimension, small samples, nonlinearity, multi-peak, etc., chaotic mapping theory is combined with parameter optimization method of support vector machine, and a kind o f chaotic v-support vector machine （SVM） named Cv-SVM is proposed. And then, a product sale forecasting method is put forward. The results of application in car sale forecasting show that the forecasting method based on Cv-SVM is effective and feasible.

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