| 复杂系统多因素估计函数分析及其应用 |
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| 引用本文： | 陈红英,王涛,毛革非.复杂系统多因素估计函数分析及其应用[J].微电子学与计算机,2012,29(6):68-70,75. |
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| 作者姓名： | 陈红英 王涛 毛革非 |
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| 作者单位： | 1. 华南师范大学计算机学院,广东广州,510631
2. 广州亿程交通信息有限公司,广东广州,510630 |
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| 基金项目： | 广东省自然科学基金项目(9451063101() |
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| 摘 要： | 复杂的系统通常有多因素与目标相关。这些因素中哪些与目标最相关,以及相关因素与目标之间的关系对复杂系统的分析很重要.首先采用基干信息熵的方法求取最关键因素.然舌对训练集进行聚类,最后采用拉格朗日多项式定义关键因素与目标之间的函数关系,并将该方法应用干智能交通系统中的行车油量分析系统,取得了较好的效果.
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| 关 键 词： | 信息熵 聚类 多项式插值 |
Complicated System Factor＇s Function Analysis and Application |
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| CHEN Hong-ying,WANG Tao,MAO Ge-fei.Complicated System Factor＇s Function Analysis and Application[J].Microelectronics & Computer,2012,29(6):68-70,75. |
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| Authors: | CHEN Hong-ying WANG Tao MAO Ge-fei |
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| Affiliation: | 1 Institute of Computer.South China Normal University.Guangzhou 510631.China; 2 YiCheng Traffic Information Corporation.Guangzhou 510630.China) |
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| Abstract: | Complicated system usually has many factors that have relation with result.Which is the most important factor,and what is the relation between these factors with result.In this paper these most important factors are found by method of information entropy,then training set is clustered,finally Lagrange interpolation method is used to find the function between important factors and result.In the end of this paper,this method is used in vehicle oil quantity analysis system,and gets satisfying effect. |
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| Keywords: | information entropy cluster lagrange interpolation method |
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