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Robust Optimization of Spline Models and Complex Regulatory Networks: Theory, Methods and Applications - Rilegato
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This book introduces methods of robust optimization in multivariateadaptive regression splines (MARS) and Conic MARS in order to handleuncertainty and non-linearity. The proposed techniques are implemented andexplained in two-model regulatory systems that can be found in the financialsector and in the contexts of banking, environmental protection, system biologyand medicine. The book provides necessarybackground information on multi-model regulatory networks, optimizationand regression. It presents the theory of and approaches to robust (conic)multivariate adaptive regression splines - R(C)MARS – and robust (conic)generalized partial linear models – R(C)GPLM – under polyhedral uncertainty. Further,it introduces spline regression models for multi-model regulatory networks andinterprets (C)MARS results based on different datasets for the implementation.It explains robust optimization in these models in terms of both the theory andmethodology. In this context it studies R(C)MARS results with differentuncertainty scenarios for a numerical example. Lastly, the book demonstratesthe implementation of the method in a number of applications from thefinancial, energy, and environmental sectors, and provides an outlook on futureresearch.
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Informazioni sull?autore
Ayse Özmen has affiliation at Turkish EnergyFoundation(TENVA)and Institute of Applied Mathematics of Middle East TechnicalUniversity (METU), Ankara, Turkey. Her research is on OR, optimization, energymodelling, renewable energy systems, network modelling, regulatory networks, datamining. She received her Doctorate in Scientific Computing at Institute forApplied Mathematics at METU.
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This book introduces methods of robust optimization in multivariateadaptive regression splines (MARS) and Conic MARS in order to handleuncertainty and non-linearity. The proposed techniques are implemented andexplained in two-model regulatory systems that can be found in the financialsector and in the contexts of banking, environmental protection, system biologyand medicine. The book provides necessarybackground information on multi-model regulatory networks, optimizationand regression. It presents the theory of and approaches to robust (conic)multivariate adaptive regression splines - R(C)MARS and robust (conic)generalized partial linear models R(C)GPLM under polyhedral uncertainty. Further,it introduces spline regression models for multi-model regulatory networks andinterprets (C)MARS results based on different datasets for the implementation.It explains robust optimization in these models in terms of both the theory andmethodology. In this context it studies R(C)MARS results with differentuncertainty scenarios for a numerical example. Lastly, the book demonstratesthe implementation of the method in a number of applications from thefinancial, energy, and environmental sectors, and provides an outlook on futureresearch.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreSpringer Verlag
- Data di pubblicazione2016
- ISBN 10 3319307991
- ISBN 13 9783319307992
- RilegaturaCopertina rigida
- LinguaInglese
- Numero edizione1
- Numero di pagine152
- Contatto del produttorenon disponibile
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Robust Optimization of Spline Models and Complex Regulatory Networks : Theory, Methods and Applications
Editore:
Springer International Publishing, 2016
ISBN 10: 3319307991
ISBN 13: 9783319307992
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Robust Optimization of Spline Models and Complex Regulatory Networks. Theory, Methods and Applications.
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Cham, Springer International Publishing; : Springer., 2016
ISBN 10: 3319307991
ISBN 13: 9783319307992
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XII, 139 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Contributions to Management Science. Sprache: Englisch. Codice articolo 6137GB
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Robust Optimization of Spline Models and Complex Regulatory Networks
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Springer International Publishing, 2016
ISBN 10: 3319307991
ISBN 13: 9783319307992
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presentsnew methods of robust optimization to handle uncertainty and non-linearity incomplex regulatory networksProvidesguidance in the trade-off between accuracy and robustnessExemplifiesthe new methods in three detailed applications involving fina. Codice articolo 117041163
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Robust Optimization of Spline Models and Complex Regulatory Networks
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Springer International Publishing Mai 2016, 2016
ISBN 10: 3319307991
ISBN 13: 9783319307992
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces methods of robust optimization in multivariateadaptive regression splines (MARS) and Conic MARS in order to handleuncertainty and non-linearity. The proposed techniques are implemented andexplained in two-model regulatory systems that can be found in the financialsector and in the contexts of banking, environmental protection, system biologyand medicine. The book provides necessarybackground information on multi-model regulatory networks, optimizationand regression. It presents the theory of and approaches to robust (conic)multivariate adaptive regression splines - R(C)MARS - and robust (conic)generalized partial linear models - R(C)GPLM - under polyhedral uncertainty. Further,it introduces spline regression models for multi-model regulatory networks andinterprets (C)MARS results based on different datasets for the implementation.It explains robust optimization in these models in terms of both the theory andmethodology. In this context it studies R(C)MARS results with differentuncertainty scenarios for a numerical example. Lastly, the book demonstratesthe implementation of the method in a number of applications from thefinancial, energy, and environmental sectors, and provides an outlook on futureresearch. 152 pp. Englisch. Codice articolo 9783319307992
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Robust Optimization of Spline Models and Complex Regulatory Networks : Theory, Methods and Applications
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Springer International Publishing, 2016
ISBN 10: 3319307991
ISBN 13: 9783319307992
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces methods of robust optimization in multivariateadaptive regression splines (MARS) and Conic MARS in order to handleuncertainty and non-linearity. The proposed techniques are implemented andexplained in two-model regulatory systems that can be found in the financialsector and in the contexts of banking, environmental protection, system biologyand medicine. The book provides necessarybackground information on multi-model regulatory networks, optimizationand regression. It presents the theory of and approaches to robust (conic)multivariate adaptive regression splines - R(C)MARS - and robust (conic)generalized partial linear models - R(C)GPLM - under polyhedral uncertainty. Further,it introduces spline regression models for multi-model regulatory networks andinterprets (C)MARS results based on different datasets for the implementation.It explains robust optimization in these models in terms of both the theory andmethodology. In this context it studies R(C)MARS results with differentuncertainty scenarios for a numerical example. Lastly, the book demonstratesthe implementation of the method in a number of applications from thefinancial, energy, and environmental sectors, and provides an outlook on futureresearch. Codice articolo 9783319307992
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Robust Optimization of Spline Models and Complex Regulatory Networks
ISBN 10: 3319307991
ISBN 13: 9783319307992
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Buch. Condizione: Neu. Neuware -This book introduces methods of robust optimization in multivariateadaptive regression splines (MARS) and Conic MARS in order to handleuncertainty and non-linearity. The proposed techniques are implemented andexplained in two-model regulatory systems that can be found in the financialsector and in the contexts of banking, environmental protection, system biologyand medicine. The book provides necessarybackground information on multi-model regulatory networks, optimizationand regression. It presents the theory of and approaches to robust (conic)multivariate adaptive regression splines - R(C)MARS ¿ and robust (conic)generalized partial linear models ¿ R(C)GPLM ¿ under polyhedral uncertainty. Furtherit introduces spline regression models for multi-model regulatory networks andinterprets (C)MARS results based on different datasets for the implementation.It explains robust optimization in these models in terms of both the theory andmethodology. In this context it studies R(C)MARS results with differentuncertainty scenarios for a numerical example. Lastly, the book demonstratesthe implementation of the method in a number of applications from thefinancial, energy, and environmental sectors, and provides an outlook on futureresearch.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 152 pp. Englisch. Codice articolo 9783319307992
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Robust Optimization of Spline Models and Complex Regulatory Networks: Theory, Methods and Applications (Contributions to Management Science)
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Robust Optimization of Spline Models and Complex Regulatory Networks: Theory, Methods and Applications (Contributions to Management Science)
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Robust Optimization of Spline Models and Complex Regulatory Networks: Theory, Methods and Applications
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