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Robust Optimization of Spline Models and Complex Regulatory Networks

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This book introduces methods of robust optimization in multivariate adaptive regression splines (MARS) and Conic MARS in order to ... Weiterlesen
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Beschreibung

This book introduces methods of robust optimization in multivariate adaptive regression splines (MARS) and Conic MARS in order to handle uncertainty and non-linearity. The proposed techniques are implemented and explained in two-model regulatory systems that can be found in the financial sector and in the contexts of banking, environmental protection, system biology and medicine. The book provides necessary background information on multi-model regulatory networks, optimization and 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 and interprets (C)MARS results based on different datasets for the implementation. It explains robust optimization in these models in terms of both the theory and methodology. In this context it studies R(C)MARS results with different uncertainty scenarios for a numerical example. Lastly, the book demonstrates the implementation of the method in a number of applications from the financial, energy, and environmental sectors, and provides an outlook on future research.



Aye 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. 

Autorentext
Aye 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. 

Klappentext
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.

Inhalt
Introduction.- Mathematical Methods Used.- New Robust Analytic Tools.- Spline Regression Models for Complex Multi-Model Regulatory Networks.- Robust Optimization in Spline Regression Models for Regulatory Networks Under Polyhedral Uncertainty.- Real-World Application with Our Robust Tools.- Conclusion and Outlook. 

Produktinformationen

Titel: Robust Optimization of Spline Models and Complex Regulatory Networks
Untertitel: Theory, Methods and Applications
Autor:
EAN: 9783319308005
ISBN: 978-3-319-30800-5
Digitaler Kopierschutz: Wasserzeichen
Format: E-Book (pdf)
Herausgeber: Springer
Genre: Wirtschaft
Anzahl Seiten: 139
Veröffentlichung: 11.05.2016
Jahr: 2016
Untertitel: Englisch
Dateigrösse: 2.8 MB

Weitere Bände aus der Buchreihe "Contributions to Management Science"