An embedded deep fuzzy association model for learning and explanation
This paper explores the complementary benefits of embedding a deep learning model as a fully data-driven fuzzy implication operator of a five-layer neuro-fuzzy system for learning and explanations for the predictions of both steady-state and dynamically changing data. In traditional Mandani-type neu...
Main Authors: | , , , |
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Other Authors: | |
Format: | Journal Article |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/164597 |