Atjaunināt sīkdatņu piekrišanu

E-grāmata: Artificial Evolution: 14th International Conference, Evolution Artificielle, EA 2019, Mulhouse, France, October 29-30, 2019, Revised Selected Papers

Edited by , Edited by , Edited by , Edited by , Edited by , Edited by
  • Formāts - PDF+DRM
  • Cena: 53,52 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

This book constitutes the thoroughly refereed post-conference proceedings of the 14th International Conference on Artificial Evolution, EA 2019, held in Mulhouse, France, in October 2019.





The 16 revised papers were carefully reviewed and selected from 33 submissions. The papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co-evolution, artificial life, population dynamics, theory, algorithmic and modeling, implementations, application of evolutionary paradigms to the real world (industry, biosciences...), other biologically-inspired paradigms (swarm, artificial ants, artificial immune systems, cultural algorithms...), memetic algorithms, multi-objective optimization, constraint handling, parallel algorithms, dynamic optimization, machine learning and hybridization with other soft computing techniques.
From Feature Selection to Continuous Optimization.- Evolving a Weighted
Combination of Text Similarities for Authorship Attribution.- Image Signal
Processor Parameter Tuning with Surrogate-assisted Particle Swarm
Optimization.- Combinatorial Surrogate-assisted Optimization for Bus Stops
Spacing Problem.- Optimization of a Checkers Player Using Neural and
Metaheuristic Approaches.- A Novel Outlook on Feature Selection as a
Multi-Objective Problem.- Fast Evolutionary Algorithm for Solving Large-scale
Multi-objective Problems.- Looking for Energy Efficient Genetic Algorithms.-
Evolving Fitness Landscapes with Complementary Fitness Functions.- Bayesian
Immigrant Diploid Genetic Algorithm for Dynamic Environments.- Ant Colony
Optimization Algorithm for a Transportation Problem in Home Health Care with
the Consideration of Carbon Emissions.- Selective Vehicle Routing Problem: A
Hybrid Genetic Algorithm Approach.- Fixed Jobs Multi-agent Scheduling Problem
with Renewable Resources.- A Study ofRecombination Operators for the Cyclic
Bandwidth Problem.- Automatic Calibration of a Farm Irrigation Model: a
Multi-modal Optimization Approach.- A Hybrid Evolutionary Algorithm for
Offl­ine UAV Path Planning.