Srikanta, Patnaik and Xin-She, Yang and Kazumi, Nakamatsu, eds. (2017) Nature-Inspired Computing and Optimization - 2017. Modeling and Optimization in Science and Technologies, 10 . Springer International Publishing, Switzerland. ISBN 9783319509204
Full text not available from this repository.Abstract
The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.
| Item Type: | Book |
|---|---|
| Subjects: | Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. Q Science > QA Mathematics > QA8.9-QA10.3 Computer science. Artificial intelligence. Computational complexity. Data structures (Computer scienc. Mathematical Logic and Formal Languages |
| Divisions: | 03-Faculty of Engineering > 21001-Engineering Science (S3) |
| Depositing User: | Users 2004 not found. |
| Date Deposited: | 07 Oct 2019 08:01 |
| Last Modified: | 07 Oct 2019 08:01 |
| URI: | http://repository.unsri.ac.id/id/eprint/10772 |
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