Fuzzy modeling and genetic algorithms for data mining and exploration:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam
Elsevier/Morgan Kaufmann
c2005
|
| Schriftenreihe: | Morgan Kaufmann series in data management systems
|
| Schlagworte: | |
| Online-Zugang: | FAW01 FAW02 Volltext |
| Beschreibung: | Includes bibliographical references and index Foundations and ideas -- Principal model types -- Approaches to model building -- Fundamental concepts of fuzzy logic -- Fundamental concepts of fuzzy systems -- Fuzzy SQL and intelligent queries -- Fuzzy clustering -- Fuzzy rule induction -- Fundamental concepts of genetic algorithms -- Genetic resource scheduling optimization -- Genetic tuning of fuzzy models Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As youll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems. You dont need a background in fuzzy modeling or genetic algorithms to benefit, for this book provides it, along with detailed instruction in methods that you can immediately put to work in your own projects. The author provides many diverse examples and also an extended example in which evolutionary strategies are used to create a complex scheduling system. * Written to provide analysts, engineers, and managers with the background and specific instruction needed to develop and implement more effective data mining systems. * Helps you to understand the trade-offs implicit in various models and model architectures. * Provides extensive coverage of fuzzy SQL querying, fuzzy clustering, and fuzzy rule induction. * Lays out a roadmap for exploring data, selecting model system measures, organizing adaptive feedback loops, selecting a model configuration, implementing a working model, and validating the final model. * In an extended example, applies evolutionary programming techniques to solve a complicated scheduling problem. * Presents examples in C, C++, Java, and easy-to-understand pseudo-code. * Extensive online component, including sample code and a complete data mining workbench |
| Beschreibung: | 1 Online-Ressource (xxi, 530 p.) |
| ISBN: | 0080470599 0121942759 9780080470597 9780121942755 |
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| 500 | |a Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As youll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems. You dont need a background in fuzzy modeling or genetic algorithms to benefit, for this book provides it, along with detailed instruction in methods that you can immediately put to work in your own projects. The author provides many diverse examples and also an extended example in which evolutionary strategies are used to create a complex scheduling system. * Written to provide analysts, engineers, and managers with the background and specific instruction needed to develop and implement more effective data mining systems. * Helps you to understand the trade-offs implicit in various models and model architectures. * Provides extensive coverage of fuzzy SQL querying, fuzzy clustering, and fuzzy rule induction. * Lays out a roadmap for exploring data, selecting model system measures, organizing adaptive feedback loops, selecting a model configuration, implementing a working model, and validating the final model. * In an extended example, applies evolutionary programming techniques to solve a complicated scheduling problem. * Presents examples in C, C++, Java, and easy-to-understand pseudo-code. * Extensive online component, including sample code and a complete data mining workbench | ||
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Datensatz im Suchindex
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| any_adam_object | |
| author | Cox, Earl |
| author_facet | Cox, Earl |
| author_role | aut |
| author_sort | Cox, Earl |
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| building | Verbundindex |
| bvnumber | BV043044839 |
| collection | ZDB-4-EBA |
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| dewey-full | 006.3/12 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/12 |
| dewey-search | 006.3/12 |
| dewey-sort | 16.3 212 |
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| discipline | Informatik |
| format | Electronic eBook |
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| id | DE-604.BV043044839 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:15:51Z |
| institution | BVB |
| isbn | 0080470599 0121942759 9780080470597 9780121942755 |
| language | English |
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| physical | 1 Online-Ressource (xxi, 530 p.) |
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| series2 | Morgan Kaufmann series in data management systems |
| spelling | Cox, Earl Verfasser aut Fuzzy modeling and genetic algorithms for data mining and exploration Earl Cox Amsterdam Elsevier/Morgan Kaufmann c2005 1 Online-Ressource (xxi, 530 p.) txt rdacontent c rdamedia cr rdacarrier Morgan Kaufmann series in data management systems Includes bibliographical references and index Foundations and ideas -- Principal model types -- Approaches to model building -- Fundamental concepts of fuzzy logic -- Fundamental concepts of fuzzy systems -- Fuzzy SQL and intelligent queries -- Fuzzy clustering -- Fuzzy rule induction -- Fundamental concepts of genetic algorithms -- Genetic resource scheduling optimization -- Genetic tuning of fuzzy models Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As youll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems. You dont need a background in fuzzy modeling or genetic algorithms to benefit, for this book provides it, along with detailed instruction in methods that you can immediately put to work in your own projects. The author provides many diverse examples and also an extended example in which evolutionary strategies are used to create a complex scheduling system. * Written to provide analysts, engineers, and managers with the background and specific instruction needed to develop and implement more effective data mining systems. * Helps you to understand the trade-offs implicit in various models and model architectures. * Provides extensive coverage of fuzzy SQL querying, fuzzy clustering, and fuzzy rule induction. * Lays out a roadmap for exploring data, selecting model system measures, organizing adaptive feedback loops, selecting a model configuration, implementing a working model, and validating the final model. * In an extended example, applies evolutionary programming techniques to solve a complicated scheduling problem. * Presents examples in C, C++, Java, and easy-to-understand pseudo-code. * Extensive online component, including sample code and a complete data mining workbench Data mining gtt Genetische algoritmen gtt Fuzzy logic gtt COMPUTERS / Database Management / Data Mining bisacsh Data mining fast Fuzzy logic fast Genetic algorithms fast Data mining Fuzzy logic Genetic algorithms Genetischer Algorithmus (DE-588)4265092-6 gnd rswk-swf Fuzzy-Logik (DE-588)4341284-1 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Wissensextraktion (DE-588)4546354-2 gnd rswk-swf Modellierung (DE-588)4170297-9 gnd rswk-swf Data Mining (DE-588)4428654-5 s Modellierung (DE-588)4170297-9 s Fuzzy-Logik (DE-588)4341284-1 s Genetischer Algorithmus (DE-588)4265092-6 s 1\p DE-604 Wissensextraktion (DE-588)4546354-2 s 2\p DE-604 http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=187188 Aggregator Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Cox, Earl Fuzzy modeling and genetic algorithms for data mining and exploration Data mining gtt Genetische algoritmen gtt Fuzzy logic gtt COMPUTERS / Database Management / Data Mining bisacsh Data mining fast Fuzzy logic fast Genetic algorithms fast Data mining Fuzzy logic Genetic algorithms Genetischer Algorithmus (DE-588)4265092-6 gnd Fuzzy-Logik (DE-588)4341284-1 gnd Data Mining (DE-588)4428654-5 gnd Wissensextraktion (DE-588)4546354-2 gnd Modellierung (DE-588)4170297-9 gnd |
| subject_GND | (DE-588)4265092-6 (DE-588)4341284-1 (DE-588)4428654-5 (DE-588)4546354-2 (DE-588)4170297-9 |
| title | Fuzzy modeling and genetic algorithms for data mining and exploration |
| title_auth | Fuzzy modeling and genetic algorithms for data mining and exploration |
| title_exact_search | Fuzzy modeling and genetic algorithms for data mining and exploration |
| title_full | Fuzzy modeling and genetic algorithms for data mining and exploration Earl Cox |
| title_fullStr | Fuzzy modeling and genetic algorithms for data mining and exploration Earl Cox |
| title_full_unstemmed | Fuzzy modeling and genetic algorithms for data mining and exploration Earl Cox |
| title_short | Fuzzy modeling and genetic algorithms for data mining and exploration |
| title_sort | fuzzy modeling and genetic algorithms for data mining and exploration |
| topic | Data mining gtt Genetische algoritmen gtt Fuzzy logic gtt COMPUTERS / Database Management / Data Mining bisacsh Data mining fast Fuzzy logic fast Genetic algorithms fast Data mining Fuzzy logic Genetic algorithms Genetischer Algorithmus (DE-588)4265092-6 gnd Fuzzy-Logik (DE-588)4341284-1 gnd Data Mining (DE-588)4428654-5 gnd Wissensextraktion (DE-588)4546354-2 gnd Modellierung (DE-588)4170297-9 gnd |
| topic_facet | Data mining Genetische algoritmen Fuzzy logic COMPUTERS / Database Management / Data Mining Genetic algorithms Genetischer Algorithmus Fuzzy-Logik Data Mining Wissensextraktion Modellierung |
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