Robust Optimization of Spline Models and Complex Regulatory Networks: Theory, Methods and Applications (Contributions to Management Science) - Tapa dura

Libro 88 de 214: Contributions to Management Science

Özmen, Ayşe

 
9783319307992: Robust Optimization of Spline Models and Complex Regulatory Networks: Theory, Methods and Applications (Contributions to Management Science)
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ISBN 10: 3319307991 ISBN 13: 9783319307992
Editorial: Springer, 2016

Sinopsis

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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Acerca del autor

Ayşe Özmen has affiliation at Turkish Energy Foundation(TENVA)and Institute of Applied Mathematics of Middle East Technical University (METU), Ankara, Turkey. Her research is on OR, optimization, energy modelling, renewable energy systems, network modelling, regulatory networks, data mining. She received her Doctorate in Scientific Computing at Institute for Applied Mathematics at METU.

De la contraportada

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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Editorial
Springer
Año de publicación
2016
Idioma
Inglés
ISBN 10 
3319307991
ISBN 13 
9783319307992
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
152
Contacto del fabricante
no disponible
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Otras ediciones populares con el mismo título

9783319808901: Robust Optimization of Spline Models and Complex Regulatory Networks: Theory, Methods and Applications (Contributions to Management Science)

Edición Destacada

ISBN 10:  3319808907 ISBN 13:  9783319808901
Editorial: Springer, 2018
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