Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools (Paperback, 1st ed. 2021)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Fuzziness and Soft Computing, 408
Release date:	April 2022
First published:	2021
Authors:	Jozsef Dombi • Orsolya Csiszar
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	173
Edition:	1st ed. 2021
ISBN-13:	978-3-03-072282-1
Categories:	Books > Reference & Interdisciplinary > Communication studies > Information theory > Cybernetics & systems theory Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks
LSN:	3-03-072282-1
Barcode:	9783030722821

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