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商品詳細
Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools. 2021 ed.
・ISBN 978-3-030-72279-1 hard EUR 149.99
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お気に入り
★★★
| 著者・編者 | Dombi, Jozsef / Csiszar, Orsolya, |
|---|---|
| シリーズ | (Studies in Fuzziness and Soft Computing) |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2021 |
| ページ数 | 173 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A02-99718＞ |
解説
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.