SFr. 135.00
€ 145.80


bestellen

Artikel-Nr. 15322299


Diesen Artikel in meine
Wunschliste
Diesen Artikel
weiterempfehlen
Diesen Preis
beobachten

Weitersagen:



Autor(en): 
  • Erick Cantú-Paz
  • Efficient and Accurate Parallel Genetic Algorithms 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  November 2000  
    Genre:  EDV / Informatik 
     
    Artificial Intelligence / C / computer science / Computer Science, general / Informatik / Mathematical theory of computation / Mechanics / Theoretische Informatik
    ISBN:  9780792372219 
    EAN-Code: 
    9780792372219 
    Verlag:  Springer EN 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  #01 - Genetic Algorithms and Evolutionary Computation  
    Dimensionen:  H 235 mm / B 155 mm / D 15 mm 
    Gewicht:  445 gr 
    Seiten:  162 
    Illustration:  XVI, 162 p. 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    As genetic algorithms (GAs) become increasingly popular, they are applied to difficult problems that may require considerable computations. In such cases, parallel implementations of GAs become necessary to reach high-quality solutions in reasonable times. But, even though their mechanics are simple, parallel GAs are complex non-linear algorithms that are controlled by many parameters, which are not well understood. Efficient and Accurate Parallel Genetic Algorithms is about the design of parallel GAs. It presents theoretical developments that improve our understanding of the effect of the algorithm's parameters on its search for quality and efficiency. These developments are used to formulate guidelines on how to choose the parameter values that minimize the execution time while consistently reaching solutions of high quality. Efficient and Accurate Parallel Genetic Algorithms can be read in several ways, depending on the readers' interests and their previous knowledge about these algorithms. Newcomers to the field will find the background material in each chapter useful to become acquainted with previous work, and to understand the problems that must be faced to design efficient and reliable algorithms. Potential users of parallel GAs that may have doubts about their practicality or reliability may be more confident after reading this book and understanding the algorithms better. Those who are ready to try a parallel GA on their applications may choose to skim through the background material, and use the results directly without following the derivations in detail. These readers will find that using the results can help them to choose the type of parallel GA that best suits their needs, without having to invest the time to implement and test various options. Once that is settled, even the most experienced users dread the long and frustrating experience of configuring their algorithms by trial and error. The guidelines contained herein will shorten dramatically the time spent tweaking the algorithm, although some experimentation may still be needed for fine-tuning. Efficient and Accurate Parallel Genetic Algorithms is suitable as a secondary text for a graduate level course, and as a reference for researchers and practitioners in industry.

      



    Wird aktuell angeschaut...
     

    Zurück zur letzten Ansicht


    AGB | Datenschutzerklärung | Mein Konto | Impressum | Partnerprogramm
    Newsletter | 1Advd.ch RSS News-Feed Newsfeed | 1Advd.ch Facebook-Page Facebook | 1Advd.ch Twitter-Page Twitter
    Forbidden Planet AG © 1999-2026
    Alle Angaben ohne Gewähr
     
    SUCHEN

     
     Kategorien
    Im Sortiment stöbern
    Genres
    Hörbücher
    Aktionen
     Infos
    Mein Konto
    Warenkorb
    Meine Wunschliste
     Kundenservice
    Recherchedienst
    Fragen / AGB / Kontakt
    Partnerprogramm
    Impressum
    © by Forbidden Planet AG 1999-2026