| The Application of Genetic Algorithms and Multidimensional Distinguishing Model in Forecasting and Evaluating Credits for Mobile Clients |
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| 作者姓名： | Li Zhan Xu Ji-sheng
School of Electronic Information Wuhan University Wuhan Hubei China |
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| 作者单位： | Li Zhan，Xu Ji-sheng
School of Electronic Information，Wuhan University，Wuhan 430072，Hubei，China |
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| 基金项目： | Guangdong Mobile Communication Company Limited Key Item(2001 and 2002) |
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| 摘 要： | To solve the arrearage problem that puzzled most of the mobile corporations, we propose an approach to forecast and evaluate the credits for mobile clients, devising a method that is of the coalescence of genetic algorithm and multidimensional distinguishing model. In the end of this paper, a result of a testing application in Zhuhai Branch, GMCC was provided. The precision of the forecasting and evaluation of the client's credit is near 90%. This study is very significant to the mobile communication corporation at all levels. The popularization of the techniques and the result would produce great benefits of both society and economy.
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The application of genetic algorithms and multidimensional distinguishing model in forecasting and evaluating credits for mobile clients |
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| Li Zhan,Xu Ji-sheng
School of Electronic Information,Wuhan University,Wuhan ,Hubei,China.The Application of Genetic Algorithms and Multidimensional Distinguishing Model in Forecasting and Evaluating Credits for Mobile Clients[J].Wuhan University Journal of Natural Sciences,2003,8(2):405-408. |
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| Authors: | Li Zhan Xu Ji-sheng |
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| Institution: | (1) School of Electronic Information, Wuhan University, 430072 Wuhan, Hubei, China |
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| Abstract: | To solve the arrearage problem that puzzled most of the mobile corporations, we propose an approach to forecast and evaluate the credits for mobile clients, devising a method that is of the coalescence of genetic algorithm and multidimensional distinguishing model. In the end of this paper, a result of a testing application in Zhuhai Branch, GMCC was provided. The precision of the forecasting and evaluation of the client's credit is near 90%. This study is very significant to the mobile communication corporation at all levels. The popularization of the techniques and the result would produce great benefits of both society and economy. |
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| Keywords: | mobile communications credit evaluation ge-netic algorithms multidimensional distinguishing model be-havior attributes |
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