Aggregating Procedure for Fuzzy Cognitive Maps

Maikel Leon Espinosa
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Abstract

In the field of Knowledge Engineering and Representation, a typical struggle encompasses transferring the Subject Matter’s expertise into computational descriptions that could be used to create digital-twin representations of a given real-world scenario. Fuzzy Cognitive Maps (FCMs) have recently gained relevant attention among multiple techniques developed with this aim. However, one issue remains, when numerous of these representations need to be combined into a unique aggregated structure, it is essential to weigh factors (such as quality) into the final form to ensure its veracity, making the process not too straightforward. This paper proposes an aggregation procedure to combine FCMs into one that represents best its contributors. The technique was utilized for solving a real-life problem, and several configurations were explored. The results are compiled and reported in this paper.
模糊认知地图的聚合程序
在知识工程和表示领域,一个典型的斗争包括将主题的专业知识转化为可用于创建给定现实世界场景的数字孪生表示的计算描述。近年来,模糊认知图(fcm)在以这一目标为目标的多种技术中得到了相关关注。然而,仍然存在一个问题,当许多这些表示需要组合成一个独特的聚合结构时,必须将因素(例如质量)权衡到最终形式中,以确保其准确性,从而使过程不太简单。本文提出了一个聚合过程,将fcm组合成一个最能代表其贡献者的fcm。该技术用于解决实际问题,并探索了几种配置。本文对实验结果进行了整理和报道。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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