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人工智能归纳学习法在逆向物流发生因素及预测的应用
http://www.100md.com 2016年2月23日 《商业经济与管理》 2007年第10期
     [22]Samir K Srivastava, Rajiv K Srivastava. A Hierarchical Model for Profit-driven Reverse Logistics Network Design [C], Second World Conference on POM and 15th Annual POM Conference, Cancun, Mexico, April 30-May 3, 2004:28-30.

    Reverse Logistics Causes and Forecast Based on the Artificial Intelligence

    Induction MethodGUO Jun-ji(School of Management, Xiamen University, Xiamen Fujian, 361005)

    Abstract: The chief problems are faced with enterprises for engaging reverse logistics are the strategic decision-making. On the base of deploying resources with reason and protecting environment, enterprise how to reduce cost, achieve considerable economic income for implementing reverse logistics? Analyzed the reverse logistics definition and its development status, discussed the induction method based on information theory, and combined with manufacturing and its relative data discussed the existing factor classification and forecast of implementing reverse logistics in this paper.

    Key words: Reverse Logistics; Information theory; Induction analysis method; forecast

    (责任编辑 郑英龙)

    注:“本文中所涉及到的图表、注解、公式等内容请以PDF格式阅读原文。”, 百拇医药(计国君)
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