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Robust optimization of spline models...
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SpringerLink (Online service)
Robust optimization of spline models and complex regulatory networks = theory, methods and applications /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Robust optimization of spline models and complex regulatory networks/ by Ayse Ozmen.
Reminder of title:
theory, methods and applications /
Author:
Ozmen, Ayse.
Published:
Cham :Springer International Publishing : : 2016.,
Description:
xii, 139 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Neural networks (Computer science) - Mathematical models. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-30800-5
ISBN:
9783319308005
Robust optimization of spline models and complex regulatory networks = theory, methods and applications /
Ozmen, Ayse.
Robust optimization of spline models and complex regulatory networks
theory, methods and applications /[electronic resource] :by Ayse Ozmen. - Cham :Springer International Publishing :2016. - xii, 139 p. :ill., digital ;24 cm. - Contributions to management science,1431-1941. - Contributions to management science..
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.
ISBN: 9783319308005
Standard No.: 10.1007/978-3-319-30800-5doiSubjects--Topical Terms:
1062500
Neural networks (Computer science)
--Mathematical models.
LC Class. No.: QA402.5 / .O96 2016
Dewey Class. No.: 519.6
Robust optimization of spline models and complex regulatory networks = theory, methods and applications /
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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.
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