Evolutionary Computation in Practice / Studies in Computational Intelligence Bd.88 (PDF)
This book is loaded with examples in which computer scientists and engineers have used evolutionary computation-programs that mimic natural evolution-to solve real problems. They aren't abstract, mathematically intensive papers, but accounts of solving...
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This book is loaded with examples in which computer scientists and engineers have used evolutionary computation-programs that mimic natural evolution-to solve real problems. They aren't abstract, mathematically intensive papers, but accounts of solving important problems, including tips from the authors on how to avoid common pitfalls, maximize the effectiveness and efficiency of the search process, and many other practical suggestions. Some of the authors have already won "Humies"-Human Competitive Results Awards-for the work described in this book. I highly recommend it as a highly concentrated source of good problem-solving approaches that are applicable to many real-world problems.
--Erik Goodman, Vice President, Red Cedar Technology, Inc.; Professor, Electrical & Computer Engineering, Michigan State University; and Founding Chair, ACM SIGEVO, the Special Interest Group on Genetic and Evolutionary Computation of the Association for Computing Machinery
- 2008, 2008, 322 Seiten, Englisch
- Herausgegeben: Tina Yu, Lawrence Davis, Cem Baydar, Rajkumar Roy
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3540757716
- ISBN-13: 9783540757719
- Erscheinungsdatum: 23.01.2008
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Grösse: 18 MB
- Mit Kopierschutz
- Vorlesefunktion
From the reviews:
"‘Evolutionary Computation in Practice’ … focuses on real-world challenges and on technology transfer from academia to industry. It is of interest to everyone working on machine learning. … is well-written, easy to read and provides a comprehensive coverage of the field. … This enables the appropriate and successful use of EC. It inspires academic researchers by demonstrating the value of their work, and guides them in their development of EC. It is an excellent contribution to the Studies in Computational Intelligence series." (Larry M. Deschaine, Genetic Programming and Evolvable Machines, Vol. 9, March, 2008)
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