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A study of dynamic fuzzy cognitive map model with group consensus based on linguistic variables

机译:基于语言变量的组共识的动态模糊认知地图模型研究

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A fuzzy cognitive map (FCM) is an analysis tool that uses a graph structure to show the causal relationships of influence factors in a decision-making system. During the decision-making process, it is reasonable for experts to use linguistic variables to express their subjective opinions. However, few studies have discussed methods for aggregating the linguistic opinions of experts to reach a group consensus in FCM. In addition, the interaction weights among the factors in FCM will usually change over time in a real environment. Therefore, we applied the learning algorithm to adjust the interaction weights among the factors in the steps of FCM, after which we proposed a dynamic fuzzy cognitive map model with group consensus based on the linguistic evaluations in this study. Finally, we presented a case study using the proposed model to illustrate the development possibility of the Internet of Things (IoT) industry in Taiwan. According to the analysis results, we found that the development prospects for the IoT industry in Taiwan are optimistic. The four key factors for IoT industry development were found to be the degree of authorization and trust, the development of application technologies, the complexity of systems and equipment and cross-platform possibility.
机译:模糊认知地图(FCM)是一种分析工具,使用图形结构来显示决策系统中影响因素的因果关系。在决策过程中,专家使用语言变量来表达他们的主观意见是合理的。然而,很少有研究已经讨论过汇总专家的语言观点,以便在FCM中达成一组共识。此外,FCM中因子之间的相互作用权重通常会随着时间的推移而变化。因此,我们应用了学习算法来调整FCM步骤中的因素之间的相互作用权重,之后我们提出了一种基于本研究语言评估的集体共识的动态模糊认知地图模型。最后,我们介绍了使用拟议模型的案例研究来说明台湾物联网(物联网)行业的发展可能性。根据分析结果,我们发现台湾物联网行业的发展前景是乐观的。由于IOT行业发展的四个关键因素被发现是授权和信任程度,应用技术的发展,系统和设备的复杂性以及跨平台的可能性。

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