Robust optimization of spline models and complex regulatory networks : theory, methods and applications / Ayşe Özmen.
2016
QA402.5
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Details
Title
Robust optimization of spline models and complex regulatory networks : theory, methods and applications / Ayşe Özmen.
Author
Özmen, Ayse, author.
ISBN
9783319308005 (electronic book)
3319308009 (electronic book)
3319307991
9783319307992
9783319307992
3319308009 (electronic book)
3319307991
9783319307992
9783319307992
Published
Switzerland : Springer, 2016.
Language
English
Description
1 online resource
Item Number
10.1007/978-3-319-30800-5 doi
Call Number
QA402.5
Dewey Decimal Classification
519.6
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
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Access limited to authorized users.
Digital File Characteristics
text file PDF
Source of Description
Online resource; title from PDF title page (EBSCO, viewed June 14, 2016).
Series
Contributions to management science.
Available in Other Form
Robust Optimization of Spline Models and Complex Regulatory Networks : Theory, Methods and Applications.
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Table of Contents
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.
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.