Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools: 408 (Studies in Fuzziness and Soft Computing, 408) - Tapa dura

Libro 174 de 183: Studies in Fuzziness and Soft Computing

Dombi, József; Csiszár, Orsolya

 
9783030722791: Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools: 408 (Studies in Fuzziness and Soft Computing, 408)

Sinopsis

The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable - and even, in many cases, more efficient. 

Fuzzy logic together with multi-criteria decision-making tools provides very powerful tools for modeling human thinking. Based on their common theoretical basis, we propose a consistent framework for modeling human thinking by using the tools of all three fields: fuzzy logic, multi-criteria decision-making, and deep learning to help reduce the black-box nature of neural models; a challenge that is of vital importance to the whole research community.


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De la contraportada

The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable and even, in many cases, more efficient. 

Fuzzy logic together with multi-criteria decision-making tools provides very powerful tools for modeling human thinking. Based on their common theoretical basis, we propose a consistent framework for modeling human thinking by using the tools of all three fields: fuzzy logic, multi-criteria decision-making, and deep learning to help reduce the black-box nature of neural models; a challenge that is of vital importance to the whole research community.


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9783030722821: Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools: 408 (Studies in Fuzziness and Soft Computing)

Edición Destacada

ISBN 10:  3030722821 ISBN 13:  9783030722821
Editorial: Springer, 2022
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