Interpretable Mamdani neuro-fuzzy model through context awareness and linguistic adaptation

作者：

Highlights：

• Interpretable Neuro-fuzzy Mamdani-type model.

• Methodology for turning Neuro-fuzzy models into white-box models.

• Binary hedge relationships of fuzzy sets.

• GGGP for the construction of semantic labels to optimized fuzzy sets.

• Methodology for the automatic construction interpretable fuzzy inference systems.

摘要

•Interpretable Neuro-fuzzy Mamdani-type model.•Methodology for turning Neuro-fuzzy models into white-box models.•Binary hedge relationships of fuzzy sets.•GGGP for the construction of semantic labels to optimized fuzzy sets.•Methodology for the automatic construction interpretable fuzzy inference systems.

论文关键词：Interpretable machine learning,Fuzzy knowledge base,Grammar-Guide Genetic Algorithms,Automatic fuzzy rule generation

论文评审过程：Received 3 May 2021, Revised 19 August 2021, Accepted 13 October 2021, Available online 5 November 2021, Version of Record 10 November 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116098