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A generic fuzzy aggregation operator: rules extraction from and insertion into artificial neural networks

机译:通用模糊聚合算子:从人工神经网络提取规则并将其插入

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摘要

Multilayered feedforward artificial neural networks (ANNs) are black boxes. Several methods have been published to extract a fuzzy system from a network, where the input–output mapping of the fuzzy system is equivalent to the mapping of the ANN. These methods are generalized by means of a new fuzzy aggregation operator. It is defined by using the activation function of a network. This fact lets to choose among several standard aggregation operators. A method to extract fuzzy rules from ANNs is presented by using this new operator. The insertion of fuzzy knowledge with linguistic hedges into an ANN is also defined thanks to this operator.
机译:多层前馈人工神经网络(ANN)是黑匣子。已经发布了几种从网络中提取模糊系统的方法,其中,模糊系统的输入-输出映射等效于ANN的映射。这些方法通过新的模糊聚合算子来概括。它是通过使用网络的激活功能来定义的。这个事实使我们可以在几个标准聚合运算符中进行选择。提出了一种使用该新算子从人工神经网络中提取模糊规则的方法。借助该运算符,还定义了将具有语言对冲的模糊知识插入ANN的方法。

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