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Explainable Neural Networks Based on Fuzzy Logic and...

Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools

József Dombi, Orsolya Csiszár
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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.
年:
2021
出版社:
Springer
语言:
english
页:
160
ISBN 10:
3030722791
ISBN 13:
9783030722791
文件:
PDF, 10.34 MB
IPFS:
CID , CID Blake2b
english, 2021
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