|
| Satz 1 von 1 |
  |
|
| |
|
Evolutionary optimization algorithms: biologically-inspired and population-based approaches to computer intelligence
| |
|
1. Person/Familie
|
Simon, Dan
|
|
Titel
|
Evolutionary optimization algorithms: biologically-inspired and population-based approaches to computer intelligence
|
|
Verantw.-ang.
|
Dan Simon
|
|
Verlagsort
|
Hoboken, New Jersey
|
|
Verlag
|
Wiley & Sons
|
|
E-Jahr
|
2013
|
|
Umfangsangabe
|
XXX, 742 S.
|
|
Andere Details zur phys. Beschr.
|
Ill., graph. Darst.
|
|
Formatangabe
|
25 cm
|
|
Weitere Angaben
|
Includes bibliographical references (pages 685-726) and index
|
|
Anm. z. Erscheinungsverm.
|
Erscheinungsjahr in Vorlageform [2013]
|
|
ISBN
|
978-0-470-93741-9 hardback
|
|
Link-Text
|
Cover 
|
|
Notation
|
68T20 
|
|
Inhaltliche Zsfg.
|
"This book is a clear and lucid presentation of Evolutionary Algorithms, with a straightforward, bottom-up approach that provides the reader with a firm grasp of the basic principles of EAs. Covering the theory, history, mathematics, and applications of evolutionary optimization algorithms, this timely and practical book offers lengthy examples, a companion website, MATLAB code, and a Solutions Manual--making it perfect for advanced undergraduates, graduates, and practicing engineers involved in engineering and computer science"--
|
|
2. Inhaltliche Zsfg.
|
"Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear (but theoretically rigorous) understanding of Evolutionary Algorithms, with an emphasis on implementation rather than models"--
|
|
Bestand
|
1
|
|
Sign-Info
|
68T20 Sim
|
|
|
Hilfe
Korb
RSS
