Table of contents
About this book
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.
Editors and affiliations
- DOI https://doi.org/10.1007/978-981-13-9263-4
- Copyright Information Springer Nature Singapore Pte Ltd. 2020
- Publisher Name Springer, Singapore
- eBook Packages Intelligent Technologies and Robotics
- Print ISBN 978-981-13-9262-7
- Online ISBN 978-981-13-9263-4
- Series Print ISSN 2524-552X
- Series Online ISSN 2524-5538
- Buy this book on publisher's site