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Robust Optimization of Spline Models and Complex Regulatory Networks

Ayşe Özmen
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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.
      Format: Paperback / softback CONTRIBUTORS: Ayşe Özmen EAN: 9783319808901 COUNTRY: Switzerland PAGES: WEIGHT: 2409 g HEIGHT: 235 cm
      PUBLISHED BY: Springer International Publishing AG DATE PUBLISHED: 2018-05-27 CITY: GENRE: BUSINESS & ECONOMICS / Operations Research, MATHEMATICS / Applied, SCIENCE / Environmental Science, TECHNOLOGY & ENGINEERING / Engineering (General) WIDTH: 155 cm SPINE:

      Book Themes:

      Operational research, Applied mathematics, Environmental science, engineering and technology, Computer modelling and simulation

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      Ayşe 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. 
      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.
      Format: Paperback / softback CONTRIBUTORS: Ayşe Özmen EAN: 9783319808901 COUNTRY: Switzerland PAGES: WEIGHT: 2409 g HEIGHT: 235 cm
      PUBLISHED BY: Springer International Publishing AG DATE PUBLISHED: 2018-05-27 CITY: GENRE: BUSINESS & ECONOMICS / Operations Research, MATHEMATICS / Applied, SCIENCE / Environmental Science, TECHNOLOGY & ENGINEERING / Engineering (General) WIDTH: 155 cm SPINE:

      Book Themes:

      Operational research, Applied mathematics, Environmental science, engineering and technology, Computer modelling and simulation

      Customer Reviews

      Be the first to write a review
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      Ayşe 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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