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A first study of fuzzy cognitive maps learning using particle swarm optimization

机译:基于粒子群算法的模糊认知图学习初探

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We introduce a new algorithm for fuzzy cognitive maps learning. The proposed approach is based on the particle swarm optimization method and it is used for the detection of proper weight matrices that lead the fuzzy cognitive map to desired steady states. For this purpose a properly defined objective function that incorporates experts' knowledge is constructed and minimized. The application of the proposed methodology to an industrial control problem supports the claim that the proposed technique is efficient and robust.
机译:我们介绍了一种用于模糊认知图学习的新算法。所提出的方法基于粒子群优化方法,并且用于检测适当的权重矩阵,从而将模糊认知图引导至所需的稳态。为此,构建并最小化了包含专家知识的正确定义的目标函数。所提出的方法论在工业控制问题上的应用支持了所提出的技术是高效且鲁棒的主张。

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