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A Fuzzy Neural Network Classifier and Its Dual Network for Adaptive Learning of Structure and Parameters

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Abstract

A novel Fuzzy Neural Network Classifier (FNNC) with high classification accuracy is proposed in this paper. To alleviate rule explosion, the adaptive learning of the structure is performed in the proposed model. The dual structure of the model is designed, and the parameter conversion method of the two models during training is offered, so the gradient descent and back propagation methods can be used to train our model without intervention. The nodes in the model are composed of fuzzy membership functions, fuzzy logic connectives, and classification categories, which make it easy to transform the trained model into fuzzy rules and provide interpretations. Finally, the methods of rule extraction and reduction are further offered, and the causality contained in the model is analyzed. Compared with several existing neuro-fuzzy models on UCI and KEEL datasets, the results indicate that the proposed FNNC can achieve high classification accuracy and meanwhile provide interpretations in the form of fuzzy rules. The proposed method can achieve high accuracy without intervention while showing the decision process, reasons, and basis for classification. Moreover, by interpretations in the form of fuzzy rules that conform to human intuition, the proposed model can help people better understand, grasp, and analyze the classification process. Therefore, it has good application prospects in the classification problems that require the model to be transparent and interpretable, especially in the high-risk decision-making fields.

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Acknowledgements

This work was supported by Defense Industrial Technology Development Program (JCKY2020601B018).

Funding

The work was supported in part by the Defense Industrial Technology Development Program, JCKY2020601B018.

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Authors and Affiliations

  1. Command & Control Engineering College, Army Engineering University of PLA, Nanjing, 210007, China

    Ke Zhang, Wen-Ning Hao, Xiao-Han Yu, Da-Wei Jin & Kun Yu

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  1. Ke Zhang
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Zhang, K., Hao, WN., Yu, XH. et al. A Fuzzy Neural Network Classifier and Its Dual Network for Adaptive Learning of Structure and Parameters. Int. J. Fuzzy Syst. 25, 1034–1054 (2023). https://doi.org/10.1007/s40815-022-01421-w

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