T Gaber
Handbook of research on machine learning innovations and trends
Gaber, T; Hassanien, AE
Authors
AE Hassanien
Abstract
Continuous improvements in technological applications have allowed more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but it increases the overall probability of technological progression.
The Handbook of Research on Machine Learning Innovations and Trends is a key resource on the latest advances and research regarding the vast range of advanced systems and applications involved in machine intelligence. Highlighting multidisciplinary studies on decision theory, intelligent search, and multi-agent systems, this publication is an ideal reference source for professionals and researchers working in the field of machine learning and its applications.
Topics Covered
The many academic areas covered in this publication include, but are not limited to:
Chaos Theory
Chaotic Systems
Decision theory
Fuzzy Logic
Granular computing
Intelligent Search
Multi-Agent Systems
Web Mining
Citation
Gaber, T., & Hassanien, A. (2017). Handbook of research on machine learning innovations and trends. Hershey: IGI Global. https://doi.org/10.4018/978-1-5225-2229-4
Book Type | Authored Book |
---|---|
Online Publication Date | Apr 3, 2017 |
Publication Date | Apr 3, 2017 |
Deposit Date | Sep 19, 2019 |
Publisher | IGI Global |
ISBN | 9781522522300 |
DOI | https://doi.org/10.4018/978-1-5225-2229-4 |
Publisher URL | http://dx.doi.org/10.4018/978-1-5225-2229-4 |
Related Public URLs | https://www.igi-global.com/gateway/ |
You might also like
Deep churn prediction method for telecommunication industry
(2023)
Journal Article
Optimized and efficient image-based IoT malware detection method
(2023)
Journal Article
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search