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Mamdani fuzzy networks with feedforward rule bases for complex systems modelling

机译:具有前馈规则库的Mamdani模糊网络,用于复杂系统建模

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This paper proposes a novel approach for modelling complex interconnected systems by means of Mamdani fuzzy networks with feedforward rule bases. The nodes in these networks are rule bases connected in a feedforward manner whereby outputs from some rule bases are fed as inputs to subsequent rule bases. The approach allows any fuzzy network of this type to be presented as an equivalent Mamdani fuzzy system by linguistic composition of its nodes. The composition process makes use of formal models for fuzzy networks, basic operations in such networks, their properties and advanced operations. These models, operations and properties are used for defining several types of networks with single or multiple horizontal levels and vertical layers. The proposed approach facilitates the understanding of complex interconnected systems by improving the transparency of their models.
机译:本文提出了一种通过带有前馈规则库的Mamdani模糊网络对复杂的互连系统建模的新颖方法。这些网络中的节点是以前馈方式连接的规则库,从而将某些规则库的输出作为输入提供给后续规则库。该方法允许通过其节点的语言组成将这种类型的任何模糊网络表示为等效的Mamdani模糊系统。合成过程利用了模糊网络的形式化模型,此类网络中的基本操作,其属性和高级操作。这些模型,操作和属性用于定义具有单个或多个水平层和垂直层的几种类型的网络。所提出的方法通过提高模型的透明度来促进对复杂互连系统的理解。

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