Nature-Inspired Computation in Engineering

Xin-She Yang (Curatore)

Springer International Publishing AG, 2018

This timely review book summarizes the state-of-the-art developments in nature-inspired optimization algorithms and their applications in engineering. Algorithms and topics include the overview and history of nature-inspired algorithms, discrete firefly algorithm, discrete cuckoo search, plant propagation algorithm, parameter-free bat algorithm, gravitational search, biogeography-based algorithm, differential evolution, particle swarm optimization and others. Applications include vehicle routing, swarming robots, discrete and combinatorial optimization, clustering of wireless sensor networks, cell formation, economic load dispatch, metamodeling, surrogated-assisted cooperative co-evolution, data fitting and reverse engineering as well as other case studies in engineering. This book will be an ideal reference for researchers, lecturers, graduates and engineers who are interested in nature-inspired computation, artificial intelligence and computational intelligence. It can also serveas a reference for relevant courses in computer science, artificial intelligence and machine learning, natural computation, engineering optimization and data mining.  

• Curatore: Xin-She Yang
• Editore: Springer International Publishing AG
• Collana: Studies in Computational Intelligence
• Anno: 2018
• Rilegatura: Paperback / softback
• Pagine: 276 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783319807577

Testo in English