Applied Nature-Inspired Computing: Algorithms and Case Studies

Nilanjan Dey (Curatore)

Amira S. Ashour (Curatore)

Springer Verlag, Singapore, 2020

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.

• Curatore: Nilanjan Dey, Amira S. Ashour
• Editore: Springer Verlag, Singapore
• Collana: Springer Tracts in Nature-Inspired Computing
• Anno: 2020
• Rilegatura: Paperback / softback
• Pagine: 275 p.
• Dimensioni: 235 x 155 mm
• EAN: 9789811392658

Testo in English