Applied Evolutionary Algorithms in Java:
Genetic algorithms provide a powerful range of methods for solving complex engineering search and optimization algorithms. Their power can also lead to difficulty for new researchers and students who wish to apply such evolution-based methods. Applied Evolutionary Algorithms in JAVA offers a practic...
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
New York, NY
Springer New York
2003
|
| Edition: | 1st ed. 2003 |
| Subjects: | |
| Online Access: | UBY01 Volltext |
| Summary: | Genetic algorithms provide a powerful range of methods for solving complex engineering search and optimization algorithms. Their power can also lead to difficulty for new researchers and students who wish to apply such evolution-based methods. Applied Evolutionary Algorithms in JAVA offers a practical, hands-on guide to applying such algorithms to engineering and scientific problems. The concepts are illustrated through clear examples, ranging from simple to more complex problems domains; all based on real-world industrial problems. Examples are taken from image processing, fuzzy-logic control systems, mobile robots, and telecommunication network optimization problems. The JAVA-based toolkit provides an easy-to-use and essential visual interface, with integrated graphing and analysis tools. Topics and features: inclusion of a complete JAVA toolkit for exploring evolutionary algorithms; strong use of visualization techniques, to increase understanding; coverage of all major evolutionary algorithms in common usage; broad range of industrially based example applications; includes examples and an appendix based on fuzzy logic |
| Physical Description: | 1 Online-Ressource (XIII, 219 p) |
| ISBN: | 9780387216157 |
| DOI: | 10.1007/978-0-387-21615-7 |
Staff View
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| index_date | 2024-07-03T16:12:21Z |
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| institution | BVB |
| isbn | 9780387216157 |
| language | English |
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| spelling | Ghanea-Hercock, Robert Verfasser aut Applied Evolutionary Algorithms in Java by Robert Ghanea-Hercock 1st ed. 2003 New York, NY Springer New York 2003 1 Online-Ressource (XIII, 219 p) txt rdacontent c rdamedia cr rdacarrier Genetic algorithms provide a powerful range of methods for solving complex engineering search and optimization algorithms. Their power can also lead to difficulty for new researchers and students who wish to apply such evolution-based methods. Applied Evolutionary Algorithms in JAVA offers a practical, hands-on guide to applying such algorithms to engineering and scientific problems. The concepts are illustrated through clear examples, ranging from simple to more complex problems domains; all based on real-world industrial problems. Examples are taken from image processing, fuzzy-logic control systems, mobile robots, and telecommunication network optimization problems. The JAVA-based toolkit provides an easy-to-use and essential visual interface, with integrated graphing and analysis tools. Topics and features: inclusion of a complete JAVA toolkit for exploring evolutionary algorithms; strong use of visualization techniques, to increase understanding; coverage of all major evolutionary algorithms in common usage; broad range of industrially based example applications; includes examples and an appendix based on fuzzy logic Programming Techniques Artificial Intelligence Algorithm Analysis and Problem Complexity Computer programming Artificial intelligence Algorithms API (DE-588)4430243-5 gnd rswk-swf Java Programmiersprache (DE-588)4401313-9 gnd rswk-swf Genetischer Algorithmus (DE-588)4265092-6 gnd rswk-swf Evolutionärer Algorithmus (DE-588)4366912-8 gnd rswk-swf Evolutionärer Algorithmus (DE-588)4366912-8 s Java Programmiersprache (DE-588)4401313-9 s API (DE-588)4430243-5 s DE-604 Genetischer Algorithmus (DE-588)4265092-6 s Erscheint auch als Druck-Ausgabe 9781468495263 Erscheint auch als Druck-Ausgabe 9780387955681 Erscheint auch als Druck-Ausgabe 9781468495256 https://doi.org/10.1007/978-0-387-21615-7 Verlag URL des Eerstveröffentlichers Volltext |
| spellingShingle | Ghanea-Hercock, Robert Applied Evolutionary Algorithms in Java Programming Techniques Artificial Intelligence Algorithm Analysis and Problem Complexity Computer programming Artificial intelligence Algorithms API (DE-588)4430243-5 gnd Java Programmiersprache (DE-588)4401313-9 gnd Genetischer Algorithmus (DE-588)4265092-6 gnd Evolutionärer Algorithmus (DE-588)4366912-8 gnd |
| subject_GND | (DE-588)4430243-5 (DE-588)4401313-9 (DE-588)4265092-6 (DE-588)4366912-8 |
| title | Applied Evolutionary Algorithms in Java |
| title_auth | Applied Evolutionary Algorithms in Java |
| title_exact_search | Applied Evolutionary Algorithms in Java |
| title_exact_search_txtP | Applied Evolutionary Algorithms in Java |
| title_full | Applied Evolutionary Algorithms in Java by Robert Ghanea-Hercock |
| title_fullStr | Applied Evolutionary Algorithms in Java by Robert Ghanea-Hercock |
| title_full_unstemmed | Applied Evolutionary Algorithms in Java by Robert Ghanea-Hercock |
| title_short | Applied Evolutionary Algorithms in Java |
| title_sort | applied evolutionary algorithms in java |
| topic | Programming Techniques Artificial Intelligence Algorithm Analysis and Problem Complexity Computer programming Artificial intelligence Algorithms API (DE-588)4430243-5 gnd Java Programmiersprache (DE-588)4401313-9 gnd Genetischer Algorithmus (DE-588)4265092-6 gnd Evolutionärer Algorithmus (DE-588)4366912-8 gnd |
| topic_facet | Programming Techniques Artificial Intelligence Algorithm Analysis and Problem Complexity Computer programming Artificial intelligence Algorithms API Java Programmiersprache Genetischer Algorithmus Evolutionärer Algorithmus |
| url | https://doi.org/10.1007/978-0-387-21615-7 |
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