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Applied nature-inspired computing : algorithms and case studies.
- Publication Year :
- 2020
-
Abstract
- Summary: This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.
- Subjects :
- Natural computation
Subjects
Details
- Language :
- English
- ISBN :
- 9789811392627 (hbk.)
- ISBNs :
- 9789811392627
- Database :
- Jio Institute Digital Library Catalog
- Journal :
- Applied nature-inspired computing : algorithms and case studies / Nilanjan Dey, Amira S. Ashour, Siddhartha Bhattacharyya, editors.
- Notes :
- Includes bibliographical references and index.
- Publication Type :
- Book
- Accession number :
- jlc.oai.folio.org.fs00001072.66c4b96a.2528.4286.b139.7effd42b10b4
- Document Type :
- Online; Non-fiction