This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments. Also presents the problem of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments.
| ISBN: | 9783319256658 |
| Publication date: | 16th December 2015 |
| Author: | Moamar SayedMouchaweh |
| Publisher: | Springer an imprint of Springer International Publishing |
| Format: | Paperback |
| Pagination: | 75 pages |
| Series: | SpringerBriefs in Applied Sciences and Technology |
| Genres: |
Artificial intelligence Communications engineering / telecommunications |
This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments.
Learning from Data Streams in Dynamic Environments features in the following genres: Artificial intelligence, Communications engineering / telecommunications
Paperback. Not Available.
Learning from Data Streams in Dynamic Environments was written by Moamar SayedMouchaweh and published by Springer an imprint of Springer International Publishing
Learning from Data Streams in Dynamic Environments has 75 pages
Yes it is part of SpringerBriefs in Applied Sciences and Technology series