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Evolutionary computation
| Evolutionary computation |
| Pubbl/distr/stampa | [Cambridge, Mass.], : MIT Press |
| Disciplina | 004 |
| Soggetto topico |
Genetic algorithms
Artificial intelligence Evolutionary computation Biological Evolution Mathematical Computing Models, Genetic Models, Theoretical Natural Computation Evolution Datenverarbeitung Zeitschrift Online-Ressource Künstliche Intelligenz Algoritmen Zoekstrategieën Computermethoden |
| Soggetto genere / forma | Periodicals. |
| ISSN | 1530-9304 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910146085603321 |
| [Cambridge, Mass.], : MIT Press | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Evolutionary computation in gene regulatory network research / / edited by Hitoshi Iba, Nasimul Noman ; contributors, Tatsuya Akutsu [and thirty others]
| Evolutionary computation in gene regulatory network research / / edited by Hitoshi Iba, Nasimul Noman ; contributors, Tatsuya Akutsu [and thirty others] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , 2016 |
| Descrizione fisica | 1 online resource (462 pages) |
| Disciplina | 572.8650113 |
| Collana |
Wiley Series in Bioinformatics: Computational Techniques and Engineering
THEi Wiley ebooks. |
| Soggetto topico |
Genetic regulation - Mathematical models
Gene regulatory networks - Computer simulation Genetic algorithms Evolutionary computation |
| ISBN |
1-119-07978-0
1-119-07977-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910137485303321 |
| Hoboken, New Jersey : , : Wiley, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Evolutionary computation in gene regulatory network research / / edited by Hitoshi Iba, Nasimul Noman ; contributors, Tatsuya Akutsu [and thirty others]
| Evolutionary computation in gene regulatory network research / / edited by Hitoshi Iba, Nasimul Noman ; contributors, Tatsuya Akutsu [and thirty others] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , 2016 |
| Descrizione fisica | 1 online resource (462 pages) |
| Disciplina | 572.8650113 |
| Collana |
Wiley Series in Bioinformatics: Computational Techniques and Engineering
THEi Wiley ebooks. |
| Soggetto topico |
Genetic regulation - Mathematical models
Gene regulatory networks - Computer simulation Genetic algorithms Evolutionary computation |
| ISBN |
1-119-07978-0
1-119-07977-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910818177103321 |
| Hoboken, New Jersey : , : Wiley, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
FOGA '09 : proceedings of the 10th ACM SIGEVO Conference on Foundations of Genetic Algorithms
| FOGA '09 : proceedings of the 10th ACM SIGEVO Conference on Foundations of Genetic Algorithms |
| Autore | Garibay Ivan |
| Pubbl/distr/stampa | [Place of publication not identified], : Association for Computing Machinery, 2009 |
| Descrizione fisica | 1 online resource (204 p.;) |
| Disciplina | 511/.6 |
| Collana | ACM Conferences |
| Soggetto topico |
Combinatorial optimization
Machine learning Genetic algorithms Civil & Environmental Engineering Engineering & Applied Sciences Operations Research |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | pt. I. Continuous optimization. Weighted recombination evolution strategy on a class of PDQF's / Steffen Finck, Hans-Georg Beyer ; Why standard particle swarm optimisers elude a theoretical runtime analysis / Carsten Witt -- pt. II. Combinatorial optimization. On the size of weights in randomized search heuristics / Joachim Reichel, Martin Skutella ; Single- and multi-objective evolutionary algorithms for graph bisectioning / Gero Greiner ; On the utility of the population size for inversely fitness proportional mutation rates / Christine Zarges ; On the impact of the mutation-selection balance on the runtime of evolutionary algorithms / Per Kristian Lehre, Xin Yao ; Computing single source shortest paths using single-objective fitness / Surender Baswana ... [et al.] ; Black-box search elimination of fitness functions / Gautham Anil, R. Paul Wiegand -- pt. III. Multi-objective optimization. Additive approximations of pareto-optimal sets by evolutionary multi-objective algorithms / Christian Horoba ; Theory of the hypervolume indicator : optimal ư-distributions and the choice of the reference point / Anne Auger ... [et al.] ; Don't be greedy when calculating hypervolume contributions / Karl Bringmann, Tobias Friedrich ; Analysis of a simple evolutionary algorithm for the multiobjective shortest path problem / Christian Horoba -- pt. IV. Co-optimization. Unbiased coevolutionary solution concepts / Travis C. Service ; Stability of learning dynamics in two-agent, imperfect-information games / John M. Butterworth, Jonathan L. Shapiro ; Cooperative coevolution and univariate estimation of distribution algorithms / Christopher Vo, Liviu Panait, Sean Luke ; Monotonicity versus performance in co-optimization / Elena Popovici, Kenneth De Jong -- pt. V. Problem analysis. A Gaussian random field model of smooth fitness landscapes / Alberto Moraglio, Yossi Borenstein ; Free lunches for function and program induction / Riccardo Poli, Mario Graff, Nicholas Freitag McPhee. |
| Altri titoli varianti | FOGA '09 |
| Record Nr. | UNINA-9910375816603321 |
Garibay Ivan
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| [Place of publication not identified], : Association for Computing Machinery, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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FOGA '11 : proceedings of the 2011 ACM/SIGEVO Foundations of Genetic Algorithms XI, January 5-9, 2011, Schwarzenberg, Austria
| FOGA '11 : proceedings of the 2011 ACM/SIGEVO Foundations of Genetic Algorithms XI, January 5-9, 2011, Schwarzenberg, Austria |
| Autore | Beyer Hans-Georg |
| Pubbl/distr/stampa | [Place of publication not identified], : Association for Computing Machinery, 2011 |
| Descrizione fisica | 1 online resource (262 p.;) |
| Collana | ACM Conferences |
| Soggetto topico |
Genetic algorithms
Civil & Environmental Engineering Engineering & Applied Sciences Operations Research |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | FOGA '11 |
| Record Nr. | UNINA-9910376510203321 |
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Beyer Hans-Georg
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| [Place of publication not identified], : Association for Computing Machinery, 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Fuzzy modeling and genetic algorithms for data mining and exploration [[electronic resource] /] / Earl Cox
| Fuzzy modeling and genetic algorithms for data mining and exploration [[electronic resource] /] / Earl Cox |
| Autore | Cox Earl |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | San Francisco, CA, : Elsevier/Morgan Kaufmann, c2005 |
| Descrizione fisica | 1 online resource (553 p.) |
| Disciplina | 006.3/12 |
| Collana | The Morgan Kaufmann series in data management systems |
| Soggetto topico |
Data mining
Fuzzy logic Genetic algorithms |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-96129-5
9786610961290 0-08-047059-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration; Copyright Page; Contents; Preface; Objectives and Audience; Organization of the Book; Algorithm Definitions and Examples; Acknowledgments; Introduction; The Modern Connected World; The Advent of Intelligent Models; Fuzzy Logic and Genetic Algorithms; Part I: Concepts and Issues; Chapter 1. Foundations and Ideas; 1.1 Enterprise Applications and Analysis Models; 1.2 Distributed and Centralized Repositories; 1.3 The Age of Distributed Knowledge; 1.4 Information and Knowledge Discovery
1.5 Data Mining and Business Models1.6 Fuzzy Systems for Business Process Models; 1.7 Evolving Distributed Fuzzy Models; 1.8 A Sample Case: Evolving a Model for Customer Segmentation; 1.9 Review; Chapter 2. Principal Model Types; 2.1 Model and Event State Categorization; 2.2 Model Type and Outcome Categorization; 2.3 Review; Chapter 3. Approaches to Model Building; 3.1 Ordinary Statistics; 3.2 Nonparametric Statistics; 3.3 Linear Regression in Statistical Models; 3.4 Nonlinear Growth Curve Fitting; 3.5 Cluster Analysis; 3.6 Decision Trees and Classifiers; 3.7 Neural Networks 3.8 Fuzzy SQL Systems3.9 Rule Induction and Dynamic Fuzzy Models; 3.10 Review; Further Reading; Part II: Fuzzy Systems; Chapter 4. Fundamental Concepts of Fuzzy Logic; 4.1 The Vocabulary of Fuzzy Logic; 4.2 Boolean (Crisp) Sets: The Law of Bivalence; 4.3 Fuzzy Sets; 4.4 Review; Chapter 5. Fundamental Concepts of Fuzzy Systems; 5.1 The Vocabulary of Fuzzy Systems; 5.2 Fuzzy Rule-based Systems: An Overview; 5.3 Variable Decomposition into Fuzzy Sets; 5.4 A Fuzzy Knowledge Base: The Details; 5.5 The Fuzzy Inference Engine; 5.6 Inference Engine Approaches; 5.7 Running a Fuzzy Model; 5.8 Review Chapter 6. Fuzzy SQL and Intelligent Queries6.1 The Vocabulary of Relational Databases and Queries; 6.2 Basic Relational Database Concepts; 6.3 Structured Query Language Fundamentals; 6.4 Precision and Accuracy; 6.5 Why We Search Databases; 6.6 Expanding the Query Scope; 6.7 Fuzzy Query Fundamentals; 6.8 Measuring Query Compatibility; 6.9 Complex Query Compatibility Metrics; 6.10 Compatibility Threshold Management; 6.11 Fuzzy SQL Process Flow; 6.12 Fuzzy SQL Example; 6.13 Evaluating Fuzzy SQL Outcomes; 6.14 Review; Chapter 7. Fuzzy Clustering; 7.1 The Vocabulary of Fuzzy Clustering 7.2 Principles of Cluster Detection7.3 Some General Clustering Concepts; 7.4 Crisp Clustering Techniques; 7.5 Fuzzy Clustering Concepts; 7.6 Fuzzy c-Means Clustering; 7.7 Fuzzy Adaptive Clustering; 7.8 Generating Rule Prototypes; 7.9 Review; Chapter 8. Fuzzy Rule Induction; 8.1 The Vocabulary of Rule Induction; 8.2 Rule Induction and Fuzzy Models; 8.3 The Rule Induction Algorithm; 8.4 The Model Building Methodology; 8.5 A Rule Induction and Model Building Example; 8.6 Measuring Model Robustness; 8.7 Technical Implementation; 8.8 External Controls; 8.9 Organization of the Knowledge Base 8.10 Review |
| Record Nr. | UNINA-9910458702303321 |
|
Cox Earl
|
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| San Francisco, CA, : Elsevier/Morgan Kaufmann, c2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Fuzzy modeling and genetic algorithms for data mining and exploration [[electronic resource] /] / Earl Cox
| Fuzzy modeling and genetic algorithms for data mining and exploration [[electronic resource] /] / Earl Cox |
| Autore | Cox Earl |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | San Francisco, CA, : Elsevier/Morgan Kaufmann, c2005 |
| Descrizione fisica | 1 online resource (553 p.) |
| Disciplina | 006.3/12 |
| Collana | The Morgan Kaufmann series in data management systems |
| Soggetto topico |
Data mining
Fuzzy logic Genetic algorithms |
| ISBN |
1-280-96129-5
9786610961290 0-08-047059-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration; Copyright Page; Contents; Preface; Objectives and Audience; Organization of the Book; Algorithm Definitions and Examples; Acknowledgments; Introduction; The Modern Connected World; The Advent of Intelligent Models; Fuzzy Logic and Genetic Algorithms; Part I: Concepts and Issues; Chapter 1. Foundations and Ideas; 1.1 Enterprise Applications and Analysis Models; 1.2 Distributed and Centralized Repositories; 1.3 The Age of Distributed Knowledge; 1.4 Information and Knowledge Discovery
1.5 Data Mining and Business Models1.6 Fuzzy Systems for Business Process Models; 1.7 Evolving Distributed Fuzzy Models; 1.8 A Sample Case: Evolving a Model for Customer Segmentation; 1.9 Review; Chapter 2. Principal Model Types; 2.1 Model and Event State Categorization; 2.2 Model Type and Outcome Categorization; 2.3 Review; Chapter 3. Approaches to Model Building; 3.1 Ordinary Statistics; 3.2 Nonparametric Statistics; 3.3 Linear Regression in Statistical Models; 3.4 Nonlinear Growth Curve Fitting; 3.5 Cluster Analysis; 3.6 Decision Trees and Classifiers; 3.7 Neural Networks 3.8 Fuzzy SQL Systems3.9 Rule Induction and Dynamic Fuzzy Models; 3.10 Review; Further Reading; Part II: Fuzzy Systems; Chapter 4. Fundamental Concepts of Fuzzy Logic; 4.1 The Vocabulary of Fuzzy Logic; 4.2 Boolean (Crisp) Sets: The Law of Bivalence; 4.3 Fuzzy Sets; 4.4 Review; Chapter 5. Fundamental Concepts of Fuzzy Systems; 5.1 The Vocabulary of Fuzzy Systems; 5.2 Fuzzy Rule-based Systems: An Overview; 5.3 Variable Decomposition into Fuzzy Sets; 5.4 A Fuzzy Knowledge Base: The Details; 5.5 The Fuzzy Inference Engine; 5.6 Inference Engine Approaches; 5.7 Running a Fuzzy Model; 5.8 Review Chapter 6. Fuzzy SQL and Intelligent Queries6.1 The Vocabulary of Relational Databases and Queries; 6.2 Basic Relational Database Concepts; 6.3 Structured Query Language Fundamentals; 6.4 Precision and Accuracy; 6.5 Why We Search Databases; 6.6 Expanding the Query Scope; 6.7 Fuzzy Query Fundamentals; 6.8 Measuring Query Compatibility; 6.9 Complex Query Compatibility Metrics; 6.10 Compatibility Threshold Management; 6.11 Fuzzy SQL Process Flow; 6.12 Fuzzy SQL Example; 6.13 Evaluating Fuzzy SQL Outcomes; 6.14 Review; Chapter 7. Fuzzy Clustering; 7.1 The Vocabulary of Fuzzy Clustering 7.2 Principles of Cluster Detection7.3 Some General Clustering Concepts; 7.4 Crisp Clustering Techniques; 7.5 Fuzzy Clustering Concepts; 7.6 Fuzzy c-Means Clustering; 7.7 Fuzzy Adaptive Clustering; 7.8 Generating Rule Prototypes; 7.9 Review; Chapter 8. Fuzzy Rule Induction; 8.1 The Vocabulary of Rule Induction; 8.2 Rule Induction and Fuzzy Models; 8.3 The Rule Induction Algorithm; 8.4 The Model Building Methodology; 8.5 A Rule Induction and Model Building Example; 8.6 Measuring Model Robustness; 8.7 Technical Implementation; 8.8 External Controls; 8.9 Organization of the Knowledge Base 8.10 Review |
| Record Nr. | UNINA-9910784647003321 |
|
Cox Earl
|
||
| San Francisco, CA, : Elsevier/Morgan Kaufmann, c2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Fuzzy modeling and genetic algorithms for data mining and exploration [[electronic resource] /] / Earl Cox
| Fuzzy modeling and genetic algorithms for data mining and exploration [[electronic resource] /] / Earl Cox |
| Autore | Cox Earl |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | San Francisco, CA, : Elsevier/Morgan Kaufmann, c2005 |
| Descrizione fisica | 1 online resource (553 p.) |
| Disciplina | 006.3/12 |
| Collana | The Morgan Kaufmann series in data management systems |
| Soggetto topico |
Data mining
Fuzzy logic Genetic algorithms |
| ISBN |
1-280-96129-5
9786610961290 0-08-047059-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration; Copyright Page; Contents; Preface; Objectives and Audience; Organization of the Book; Algorithm Definitions and Examples; Acknowledgments; Introduction; The Modern Connected World; The Advent of Intelligent Models; Fuzzy Logic and Genetic Algorithms; Part I: Concepts and Issues; Chapter 1. Foundations and Ideas; 1.1 Enterprise Applications and Analysis Models; 1.2 Distributed and Centralized Repositories; 1.3 The Age of Distributed Knowledge; 1.4 Information and Knowledge Discovery
1.5 Data Mining and Business Models1.6 Fuzzy Systems for Business Process Models; 1.7 Evolving Distributed Fuzzy Models; 1.8 A Sample Case: Evolving a Model for Customer Segmentation; 1.9 Review; Chapter 2. Principal Model Types; 2.1 Model and Event State Categorization; 2.2 Model Type and Outcome Categorization; 2.3 Review; Chapter 3. Approaches to Model Building; 3.1 Ordinary Statistics; 3.2 Nonparametric Statistics; 3.3 Linear Regression in Statistical Models; 3.4 Nonlinear Growth Curve Fitting; 3.5 Cluster Analysis; 3.6 Decision Trees and Classifiers; 3.7 Neural Networks 3.8 Fuzzy SQL Systems3.9 Rule Induction and Dynamic Fuzzy Models; 3.10 Review; Further Reading; Part II: Fuzzy Systems; Chapter 4. Fundamental Concepts of Fuzzy Logic; 4.1 The Vocabulary of Fuzzy Logic; 4.2 Boolean (Crisp) Sets: The Law of Bivalence; 4.3 Fuzzy Sets; 4.4 Review; Chapter 5. Fundamental Concepts of Fuzzy Systems; 5.1 The Vocabulary of Fuzzy Systems; 5.2 Fuzzy Rule-based Systems: An Overview; 5.3 Variable Decomposition into Fuzzy Sets; 5.4 A Fuzzy Knowledge Base: The Details; 5.5 The Fuzzy Inference Engine; 5.6 Inference Engine Approaches; 5.7 Running a Fuzzy Model; 5.8 Review Chapter 6. Fuzzy SQL and Intelligent Queries6.1 The Vocabulary of Relational Databases and Queries; 6.2 Basic Relational Database Concepts; 6.3 Structured Query Language Fundamentals; 6.4 Precision and Accuracy; 6.5 Why We Search Databases; 6.6 Expanding the Query Scope; 6.7 Fuzzy Query Fundamentals; 6.8 Measuring Query Compatibility; 6.9 Complex Query Compatibility Metrics; 6.10 Compatibility Threshold Management; 6.11 Fuzzy SQL Process Flow; 6.12 Fuzzy SQL Example; 6.13 Evaluating Fuzzy SQL Outcomes; 6.14 Review; Chapter 7. Fuzzy Clustering; 7.1 The Vocabulary of Fuzzy Clustering 7.2 Principles of Cluster Detection7.3 Some General Clustering Concepts; 7.4 Crisp Clustering Techniques; 7.5 Fuzzy Clustering Concepts; 7.6 Fuzzy c-Means Clustering; 7.7 Fuzzy Adaptive Clustering; 7.8 Generating Rule Prototypes; 7.9 Review; Chapter 8. Fuzzy Rule Induction; 8.1 The Vocabulary of Rule Induction; 8.2 Rule Induction and Fuzzy Models; 8.3 The Rule Induction Algorithm; 8.4 The Model Building Methodology; 8.5 A Rule Induction and Model Building Example; 8.6 Measuring Model Robustness; 8.7 Technical Implementation; 8.8 External Controls; 8.9 Organization of the Knowledge Base 8.10 Review |
| Record Nr. | UNINA-9910825426603321 |
|
Cox Earl
|
||
| San Francisco, CA, : Elsevier/Morgan Kaufmann, c2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Fuzzy modeling and genetic algorithms for data mining and exploration / Earl Cox
| Fuzzy modeling and genetic algorithms for data mining and exploration / Earl Cox |
| Autore | Cox, Earl |
| Pubbl/distr/stampa | San Francisco, Calif. : Elsevier/Morgan Kaufmann, c2005 |
| Descrizione fisica | xxi, 530 p. : ill. ; 24 cm |
| Disciplina | 006.312 |
| Collana | The Morgan Kaufmann series in data management systems |
| Soggetto topico |
Data mining
Fuzzy logic Genetic algorithms |
| ISBN | 0121942759 |
| Classificazione | LC QA9.64.C69 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991001580519707536 |
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Cox, Earl
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| San Francisco, Calif. : Elsevier/Morgan Kaufmann, c2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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GECCO 2007 : Genetic and Evolutionary Computation Conference, July 7-11, 2007 University College London, London, UK
| GECCO 2007 : Genetic and Evolutionary Computation Conference, July 7-11, 2007 University College London, London, UK |
| Autore | Lipson Hod |
| Pubbl/distr/stampa | [Place of publication not identified], : Association for Computing Machinery, 2007 |
| Descrizione fisica | 1 online resource (2313 p.;) |
| Disciplina | 006.3/1 |
| Collana | ACM Conferences |
| Soggetto topico |
Genetic programming (Computer science) - Data processing
Genetic algorithms Evolutionary computation Parallel processing (Electronic computers) Engineering & Applied Sciences Computer Science |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | GECCO '07 |
| Record Nr. | UNINA-9910376415703321 |
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Lipson Hod
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| [Place of publication not identified], : Association for Computing Machinery, 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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