Benchmarking main activation functions in fuzzy cognitive maps2

被引：239

作者：

Bueno, Salvador ^{[1
]}

Salmeron, Jose L. ^{[1
]}

机构：

[1] Univ Pablo Olavide, Seville 41013, Spain

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2009年 / 36卷 / 03期

关键词：

Decision support systems; Fuzzy cognitive maps; Activation functions; Benchmarking; MULTIOBJECTIVE OPTIMIZATION; DECISION-MAKING; DELPHI METHOD; MANAGEMENT; DESIGN; TECHNOLOGY; DIAGNOSIS; MODELS; ERP;

D O I：

10.1016/j.eswa.2008.06.072

中图分类号：

TP18 [人工智能理论];

学科分类号：

140502 [人工智能];

摘要：

Fuzzy cognitive maps (FCM) are graph-based modeling tools. FCM can to be used for structuring and supporting decisional processes. Also, FCM allow developing what-if analysis, through the definition of scenarios. It is possible to choose among four activation functions: (1) sigmoid function, (2) hyperbolic tangent function, (3) step function and (4) threshold linear function. The use of each function can provide different alternatives. In this context, the main objective of the present study is to develop a benchmarking analysis among the mentioned functions using a same decisional model. Findings show how the sigmoid function offers significantly greater advantages than the other functions. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：5221 / 5229

页数：9

共 49 条

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The impact of ERP on supply chain management:: Exploratory findings from a European Delphi study [J].