The Practical Handbook of Genetic Algorithms : New Frontiers, Volume II
Language: English
Published by Taylor & Francis Inc Aug 1995, 1995
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 259.13
Quantity: 2 available
Add to basketItem description from seller
Neuware - The mathematics employed by genetic algorithms (GAs)are among the most exciting discoveries of the last few decades. But what exactly 'is 'a genetic algorithm A genetic algorithm is a problem-solving method that uses genetics as its model of problem solving. It applies the rules of reproduction, gene crossover, and mutation to pseudo-organisms so those 'organisms' can pass beneficial and survival-enhancing traits to new generations. GAs are useful in the selection of parameters to optimize a system's performance. A second potential use lies in testing and fitting quantitative models. Unlike any other book available, this interesting new text/reference takes you from the construction of a simple GA to advanced implementations. As you come to understand GAs and their processes, you will begin to understand the power of the genetic-based problem-solving paradigms that lie behind them.
Seller Inventory # 9780849325298
- Title
- The Practical Handbook of Genetic Algorithms : New Frontiers, Volume II
- Author
- Lance D. Chambers
- Publisher
- Taylor & Francis Inc Aug 1995
- Publication year
- 1995
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 0849325293
- ISBN 13
- 9780849325298
- Item weight
- 844 grams
- Dimensions
- 242x166x33 mm
The mathematics employed by genetic algorithms (GAs)are among the most exciting discoveries of the last few decades. But what exactly is a genetic algorithm? A genetic algorithm is a problem-solving method that uses genetics as its model of problem solving. It applies the rules of reproduction, gene crossover, and mutation to pseudo-organisms so those "organisms" can pass beneficial and survival-enhancing traits to new generations. GAs are useful in the selection of parameters to optimize a system's performance. A second potential use lies in testing and fitting quantitative models. Unlike any other book available, this interesting new text/reference takes you from the construction of a simple GA to advanced implementations. As you come to understand GAs and their processes, you will begin to understand the power of the genetic-based problem-solving paradigms that lie behind them.
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