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Linguistic composition based modelling by fuzzy networks with modular rule bases

机译：具有模块化规则库的基于模糊网络的语言组合建模

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This paper proposes a linguistic composition based modelling approach by networked fuzzy systems that are known as fuzzy networks. The nodes in these networks are modules of fuzzy rule bases and the connections between these modules are the outputs from some rule bases that are fed as inputs to other rule bases. The proposed approach represents a fuzzy network as an equivalent fuzzy system by linguistic composition of the network nodes. In comparison to the known multiple rule base approaches, this networked rule base approach reflects adequately the structure of the modelled process in terms of interacting sub-processes and leads to more flexible solutions. The approach improves significantly the transparency of the associated model while ensuring a high level of accuracy that is comparable to the one achieved by established approaches. Another advantage of this fuzzy network approach is that it fits well within the existing approaches with single rule base and multiple rule bases. (C) 2014 Elsevier B.V. All rights reserved.
机译：本文提出了一种通过网络模糊系统（称为模糊网络）基于语言组合的建模方法。这些网络中的节点是模糊规则库的模块，并且这些模块之间的连接是某些规则库的输出，这些规则库的输入作为其他规则库的输入。所提出的方法通过网络节点的语言组成将模糊网络表示为等效的模糊系统。与已知的多个规则库方法相比，此网络规则库方法在交互子过程方面充分反映了建模过程的结构，并导致了更灵活的解决方案。该方法显着提高了关联模型的透明度，同时确保了与已建立方法所达到的准确性相当的高水平准确性。这种模糊网络方法的另一个优点是，它非常适合具有单个规则库和多个规则库的现有方法。 （C）2014 Elsevier B.V.保留所有权利。

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