托普西斯
熵(时间箭头)
计算机科学
选择(遗传算法)
理想溶液
数据挖掘
排名(信息检索)
层次分析法
最大熵原理
数学
加权
Kullback-Leibler散度
数学优化
人工智能
出处
期刊:IEEE Conference on Cybernetics and Intelligent Systems
日期:2008-09-01
被引量:25
标识
DOI:10.1109/iccis.2008.4670971
摘要
This study proposes a combined entropy weight and TOPSIS method for information system selection. In the present paper, information entropy is employed to derive the objective weights of the evaluation criteria, and a modified TOPSIS method is employed to rank a finite number of feasible alternatives in order of preference and then select a suitable information system that conforms to the decision maker’s ideal. An empirical study demonstrated the feasibility and practicability of the proposed method for real-world applications. The result shows that the approach is computationally simple and its underlying concept is rational and comprehensible, thus facilitating its implementation in a computer-based system.
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