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Applications of Evolutionary Computation: Lecture Notes in Computer Science, cartea 9028

Editat de Antonio M. Mora, Giovanni Squillero
en Limba Engleză Paperback – 30 mar 2015
This book constitutes the refereed conference proceedings of the 18th International Conference on the Applications of Evolutionary Computation, EvoApplications 2015, held in Copenhagen, Spain, in April 2015, colocated with the Evo 2015 events EuroGP, EvoCOP, and EvoMUSART. The 72 revised full papers presented were carefully reviewed and selected from 125 submissions. EvoApplications 2015 consisted of the following 13 tracks: EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary computation in robotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).
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Specificații

ISBN-13: 9783319165486
ISBN-10: 3319165488
Pagini: 944
Ilustrații: XXVII, 913 p. 304 illus.
Dimensiuni: 155 x 235 x 51 mm
Greutate: 1.4 kg
Ediția:2015
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

Evolutionary computation, machine learning and data mining in computational biology.- Nature-inspired techniques for telecommunication networks and other parallel and distributed systems.- Evolutionary algorithms and complex systems.- Evolutionary computation in energy applications.- Evolutionary and natural computation in finance and economics.- Bio-inspired algorithms in games.- Evolutionary computation in image analysis, signal processing, and pattern recognition.- Nature-inspired techniques in industrial settings.- Bio-inspired algorithms for continuous parameter optimization.- Parallel implementation of evolutionary algorithms.- Computational intelligence for risk management, security and defence applications.- Evolutionary computation in robotics.- Evolutionary algorithms in stochastic and dynamic environments.