Dynamic Fuzzy Machine Learning / (Record no. 84452)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04893nam a22008295i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 9783110520651 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730161559.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 210830t20172018gw fo d z eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783110520651 |
| 041 0# - LANGUAGE CODE | |
| Language code of text/sound track or separate title | |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.31 |
| 084 ## - OTHER CLASSIFICATION NUMBER | |
| -- | (DE-625)rvk/143663: |
| 100 1# - AUTHOR NAME | |
| Author | Li, Fanzhang, |
| 245 10 - TITLE STATEMENT | |
| Title | Dynamic Fuzzy Machine Learning / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 online resource (XIV, 323 p.) |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Fanzhang, Li, |
| 700 1# - AUTHOR 2 | |
| Author 2 | Zhang, Li, |
| 700 1# - AUTHOR 2 | |
| Author 2 | Zhang, Zhao, |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1515/9783110520651 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://www.degruyter.com/isbn/9783110520651 |
| 856 42 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://www.degruyter.com/cover/covers/9783110520651.jpg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Berlin ; |
| -- | Boston : |
| -- | De Gruyter, |
| -- | [2017] |
| 264 #4 - | |
| -- | ©2018 |
| 336 ## - | |
| -- | text |
| -- | txt |
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| -- | computer |
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| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
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| -- | rda |
| 588 0# - | |
| -- | Description based on online resource; title from PDF title page (publisher's Web site, viewed 30. Aug 2021) |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Fuzzy logic. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Machine learning. |
| 650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | COMPUTERS / Intelligence (AI) & Semantics. |
| 912 ## - | |
| -- | 978-3-11-062526-4 EBOOK PACKAGE COMPLETE ENGLISH 2017 |
| -- | 2017 |
| 912 ## - | |
| -- | 978-3-11-071955-0 DG Plus eBook-Package 2018 |
| -- | 2018 |
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| -- | ZDB-23-DEI |
| -- | 2017 |
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| -- | ZDB-23-DGG |
| -- | 2017 |
No items available.