| Title | : | Applied Nature-Inspired Computing: Algorithms and Case Studies |
|---|---|---|
| Author | : | Nilanjan Dey, Amira S. Ashour & Siddhartha Bhattacharyya |
| Release | : | 2019-08-10 |
| Kind | : | ebook |
| Genre | : | Computers & Internet, Books, Professional & Technical, Engineering, Programming, Computers, Science & Nature, Mathematics |
| Size | : | 26958661 |
| 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. |
