Squillero / Mora | Applications of Evolutionary Computation | Buch | 978-3-319-16548-6 | sack.de

Buch, Englisch, Band 9028, 913 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1399 g

Reihe: Lecture Notes in Computer Science

Squillero / Mora

Applications of Evolutionary Computation

18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings
2015
ISBN: 978-3-319-16548-6
Verlag: Springer International Publishing

18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings

Buch, Englisch, Band 9028, 913 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1399 g

Reihe: Lecture Notes in Computer Science

ISBN: 978-3-319-16548-6
Verlag: Springer International Publishing


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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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.



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