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

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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.

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Product Description

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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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Studies in Fuzziness and Soft Computing, 408

Release date

April 2021

Availability

Expected to ship within 12 - 17 working days

First published

2021

Authors

,

Dimensions

235 x 155mm (L x W)

Format

Hardcover

Pages

173

Edition

1st ed. 2021

ISBN-13

978-3-03-072279-1

Barcode

9783030722791

Categories

LSN

3-03-072279-1



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