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Research on the Application of T-S Fuzzy Neural Network in Quantitative Identification of Mixed Gas

机译:T-S模糊神经网络在混合气体定量识别中的应用研究

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This article integrated rule expression capacity of fuzzy logic inference with self-learning ability of the neural network, proposed to build Takagi-Sugeno fuzzy neural network's quantitative identification of mixed gas by combining T-S fuzzy neural network with neural network. The results indicated that this system has generalization, learning, mapping capabilities. It can better realize quantitative identification of mixed gas. This system will provide method for intelligent identification of mixed gas.
机译:本文将模糊逻辑推理的规则表达能力与神经网络的自学习能力相结合,提出将T-S模糊神经网络与神经网络相结合,建立Takagi-Sugeno模糊神经网络对混合气体的定量识别的方法。结果表明,该系统具有泛化,学习,映射功能。可以更好地实现混合气体的定量鉴定。该系统将提供智能识别混合气体的方法。

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