Isbn: 9783030063092 - extensions of dynamic programming for combinatorial optimization and data mining: 146 (intelligent systems reference library) (13 resultados)

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining (Intelligent Systems Reference Library, 146)
AbouEisha, Hassan; Amin, Talha; Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail
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Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining: 146 (Intelligent Systems Reference Library)
AbouEisha, Hassan; Amin, Talha; Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail
Idioma: Inglés
Editorial: Springer, 2019
Serie: Libro 119 de 188 - Intelligent Systems Reference Library
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Taschenbuch. Condición: Neu. Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining | Hassan Aboueisha (u. a.) | Taschenbuch | Intelligent Systems Reference Library | xvi | Englisch | 2019 | Springer | EAN 9783030063092 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Dynamic programming is an efficient technique for solving optimization problems. It is based on breaking the initial problem down into simpler ones and solving these sub-problems, beginning with the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. This book develops extensions of dynamic programming, enabling us to (i) describe the set of objects under consideration; (ii) perform a multi-stage optimization of objects relative to different criteria; (iii) count the number of optimal objects; (iv) find the set of Pareto optimal points for bi-criteria optimization problems; and (v) to study relationships between two criteria. It considers various applications, including optimization of decision trees and decision rule systems as algorithms for problem solving, as ways for knowledge representation, and as classifiers; optimization of element partition trees for rectangular meshes, which are used in finite element methods for solving PDEs; and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths. The results presented are useful for researchers in combinatorial optimization, data mining, knowledge discovery, machine learning, and finite element methods, especially those working in rough set theory, test theory, logical analysis of data, and PDE solvers. This book can be used as the basis for graduate courses.…

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining (Intelligent Systems Reference Library, 146)
AbouEisha, Hassan, Amin, Talha, Chikalov, Igor, Hussain, Sha
Idioma: Inglés
Editorial: Springer, 2019
Serie: Libro 119 de 188 - Intelligent Systems Reference Library
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Dynamic programming is an efficient technique for solving optimization problems. It is based on breaking the initial problem down into simpler ones and solving these sub-problems, beginning with the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. This book develops extensions of dynamic programming, enabling us to (i) describe the set of objects under consideration; (ii) perform a multi-stage optimization of objects relative to different criteria; (iii) count the number of optimal objects; (iv) find the set of Pareto optimal points for bi-criteria optimization problems; and (v) to study relationships between two criteria. It considers various applications, including optimization of decision trees and decision rule systems as algorithms for problem solving, as ways for knowledge representation, and as classifiers; optimization of element partition trees for rectangular meshes, which are used in finite element methods for solving PDEs; and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths. The results presented are useful for researchers in combinatorial optimization, data mining, knowledge discovery, machine learning, and finite element methods, especially those working in rough set theory, test theory, logical analysis of data, and PDE solvers. This book can be used as the basis for graduate courses. 296 pp. Englisch.…

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining: 146 (Intelligent Systems Reference Library)
AbouEisha, Hassan; Amin, Talha; Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail
Idioma: Inglés
Editorial: Springer, 2019
Serie: Libro 119 de 188 - Intelligent Systems Reference Library
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Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining
Hassan AbouEisha|Talha Amin|Igor Chikalov|Shahid Hussain|Mikhail Moshkov
Idioma: Inglés
Editorial: Springer International Publishing, 2019
Serie: Libro 119 de 188 - Intelligent Systems Reference Library
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents different dynamic programming applications in the areas of (i) optimization of decision trees, (ii) optimization of decision rules and systems of decision rules, (iii) optimization of element partition trees, which are used in finite elem. …

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining: 146 (Intelligent Systems Reference Library)
AbouEisha, Hassan; Amin, Talha; Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail
Idioma: Inglés
Editorial: Springer, 2019
Serie: Libro 119 de 188 - Intelligent Systems Reference Library
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Dynamic programming is an efficient technique for solving optimization problems. It is based on breaking the initial problem down into simpler ones and solving these sub-problems, beginning with the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. This book develops extensions of dynamic programming, enabling us to (i) describe the set of objects under consideration; (ii) perform a multi-stage optimization of objects relative to different criteria; (iii) count the number of optimal objects; (iv) find the set of Pareto optimal points for bi-criteria optimization problems; and (v) to study relationships between two criteria. It considers various applications, including optimization of decision trees and decision rule systems as algorithms for problem solving, as ways for knowledge representation, and as classifiers; optimization of element partition trees for rectangular meshes, which are used in finite element methods for solving PDEs; and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths. The results presented are useful for researchers in combinatorial optimization, data mining, knowledge discovery, machine learning, and finite element methods, especially those working in rough set theory, test theory, logical analysis of data, and PDE solvers. This book can be used as the basis for graduate courses.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 296 pp. Englisch.…