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Robust Optimization of Spline Models and Complex Regulatory Networks

Theory, Methods and Applications

Ayşe Özmen (Autor)

Buch | Hardcover

XII, 139 Seiten

2016 | 1st ed. 2016
Springer International Publishing (Verlag)
978-3-319-30799-2 (ISBN)

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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.

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.

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.

Erscheinungsdatum	08.10.2016
Reihe/Serie	Contributions to Management Science
Zusatzinfo	XII, 139 p. 22 illus., 20 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Wirtschaft ► Allgemeines / Lexika
Themenwelt	Wirtschaft ► Betriebswirtschaft / Management
Schlagworte	Appl.Mathematics/Computational Methods of Engineer • business and management • complex multi-modal regulatory networks • conic quadratic programming • Math. Appl. in Environmental Science • Mathematical Modeling and Industrial Mathematics • Operation Research/Decision Theory • Optimization • polyhedral uncertainty • robust conic optimization • robust generalized partial linear models • robust multivariate adaptive regression splines
ISBN-10	3-319-30799-1 / 3319307991
ISBN-13	978-3-319-30799-2 / 9783319307992
Zustand	Neuware