Artificial Neural Nets and Genetic Algorithms - Info and Reading Options
Proceedings of the International Conference in Roanne, France, 2003
By David W. Pearson
"Artificial Neural Nets and Genetic Algorithms" was published by Springer in 2003 - Wien, the book is classified in Computers genre, it has 266 pages and the language of the book is English.
“Artificial Neural Nets and Genetic Algorithms” Metadata:
- Title: ➤ Artificial Neural Nets and Genetic Algorithms
- Author: David W. Pearson
- Language: English
- Number of Pages: 266
- Is Family Friendly: Yes - No Mature Content
- Publisher: Springer
- Publish Date: 2003
- Publish Location: Wien
- Genres: Computers
“Artificial Neural Nets and Genetic Algorithms” Subjects and Themes:
- Subjects: ➤ Neural networks (Computer science) - Genetic algorithms - Congresses - Engineering - Physics - Computer science - Artificial intelligence - Neural networks (computer science) - Conference papers and proceedings
Edition Specifications:
- Pagination: x, 266 p. :
Edition Identifiers:
- Google Books ID: 3haO5vOc12cC
- The Open Library ID: OL3707515M - OL18286248W
- Online Computer Library Center (OCLC) ID: 52348601
- Library of Congress Control Number (LCCN): 2003279443
- ISBN-13: 9783211007433
- ISBN-10: 3211007431
- All ISBNs: 3211007431 - 9783211007433
AI-generated Review of “Artificial Neural Nets and Genetic Algorithms”:
Snippets and Summary:
The papers in this volume present theoretical aspects and applications of artificial neural networks and genetic algorithms. Also included are papers on fuzzy logic, soft computing, and artificial intelligence.
"Artificial Neural Nets and Genetic Algorithms" Description:
Google Books:
The papers in this volume present theoretical aspects and applications of artificial neural networks and genetic algorithms. Also included are papers on fuzzy logic, soft computing, and artificial intelligence. Fundamental issues are addressed, such as the nonlinear approximation capabilities of neural networks and formal methods of data representation with topological properties. New elements in genetic algorithms are presented, for example, crossover methods and gene representation. Papers on applications of neural networks show how successful these methods are in a wide range of fields like meteorological and atmospheric pollution forecasts, furnace control, and system identification. Genetic algorithms are used to solve optimization problems related to shipping and computer vision. Fuzzy-logic-based techniques are applied to sociodynamic models and hybrid neuro-fuzzy models.
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- Public Domain: No
- Availability Status: Partially available
- Availability Status for country: US.
- Available Formats: Text is not avialbe, image copy is available.
- Google Books Link: Google Books
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