Andreas B?rmann develops novel approaches for the solution of network design problems as they arise in various contexts of applied optimization. At the example of an optimal expansion of the German railway network until 2030, the author derives a tailor-made decomposition technique for multi-period network design problems. Next, he develops a general framework for the solution of network design problems via aggregation of the underlying graph structure. This approach is shown to save much computation time as compared to standard techniques. Finally, the author devises a modelling framework for the approximation of the robust counterpart under ellipsoidal uncertainty, an often-studied case in the literature. Each of these three approaches opens up a fascinating branch of research which promises a better theoretical understanding of the problem and an increasing range of solvable application settings at the same time.
This book is the first of a series which focuses on the interpolation and extrapolation of optimal designs, an area with significant applications in engineering, physics, chemistry and most experimental fields.
In this volume, the authors emphasize the importance of problems associated with the construction of design. After a brief introduction on how the theory of optimal designs meets the theory of the uniform approximation of functions, the authors introduce the basic elements to design planning and link the statistical theory of optimal design and the theory of the uniform approximation of functions.
The appendices provide the reader with material to accompany the proofs discussed throughout the book.
Автор: Fasshauer Gregory E Et Al Название: Kernel-Based Approximation Methods Using Matlab ISBN: 9814630136 ISBN-13(EAN): 9789814630139 Издательство: World Scientific Publishing Рейтинг: Цена: 11246.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In an attempt to introduce application scientists and graduate students to the exciting topic of positive definite kernels and radial basis functions, this book presents modern theoretical results on kernel-based approximation methods and demonstrates their implementation in various settings. The authors explore the historical context of this fascinating topic and explain recent advances as strategies to address long-standing problems. Examples are drawn from fields as diverse as function approximation, spatial statistics, boundary value problems, machine learning, surrogate modeling and finance. Researchers from those and other fields can recreate the results within using the documented MATLAB code, also available through the online library. This combination of a strong theoretical foundation and accessible experimentation empowers readers to use positive definite kernels on their own problems of interest.
Описание: Christian Kuchler studies various aspects of the stability of stochastic optimization problems as well as approximation and decomposition methods in stochastic programming. In particular, the author presents an extension of the Nested Benders decomposition algorithm related to the concept of recombining scenario trees.
Автор: Emmanuil H Georgoulis; Armin Iske; Jeremy Levesley Название: Approximation Algorithms for Complex Systems ISBN: 3642266657 ISBN-13(EAN): 9783642266652 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Part I INVITED SURVEYS: Emergent Behaviour in Large Electrical Networks by D. P. Almond, C.J. Budd, N.J. McCullen.- Algorithms and Error Bounds for Multivariate Piecewise Constant Approximation by O. Davydov.- Anisotropic Triangulation Methods in Adaptive Image Approximation by L. Demaret, A. Iske.- Form Assessment in Coordinate Metrology by A.B. Forbes and H.D.Minh.- Discontinuous Galerkin Methods for Linear Problems: An Introduction by E. H. Georgoulis.- A Numerical Analyst's View of the Lattice Boltzmann Method by A. G. Gorban, J. Levesley, D. Packwood.- Approximating Probability Measures on Manifolds via Radial Basis Functions by J. Levesley, X. Sun.- Part II CONTRIBUTED RESEARCH PAPERS: Modelling Clinical Decay Data Using Exponential Functions by M.G. Cox.- Towards Calculating the Basin of Attraction of Non-Smooth Dynamical Systems Using Radial Basis Functions by P. Giesl.- Stabilizing Lattice Boltzmann Simulation of Fluid Flow past a Circular Cylinder with Ehrenfests' Limiter by T.S. Khan, J. Levesley.- Fast and Stable Interpolation of Well Data Using the Norm Function by B. Li, J. Levesley.- Algorithms and Literate Programs for Weighted Low-Rank Approximation with Missing Data by I. Markovsky.- On Bivariate Interpolatory Mask Symbols, Subdivision and Refinable Functions by A. F. Rabarison, J. de Villiers.- Model and Feature Selection in Metrology Data Approximation by X. Yang, A. B. Forbes.
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