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Optimization of Stochastic Heat Engines in the Underdamped Limit, Nikolas Z?ller


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Автор: Nikolas Z?ller
Название:  Optimization of Stochastic Heat Engines in the Underdamped Limit
ISBN: 9783658163495
Издательство: Springer
Классификация:


ISBN-10: 3658163496
Обложка/Формат: Paperback
Страницы: 91
Вес: 0.13 кг.
Дата издания: 09.01.2017
Серия: BestMasters
Язык: English
Издание: 1st ed. 2017
Иллюстрации: 33 illustrations, black and white; ix, 91 p. 33 illus.
Размер: 210 x 148 x 6
Читательская аудитория: Professional & vocational
Основная тема: Physics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Nikolas Zoller examines the working principles and the underlying theoretical foundations of a microscopic heat engine. In particular, he investigates the system`s stochastic dynamics in the underdamped regime which has hardly been studied in the past, but will be experimentally feasible in the near future due to recent technological developments.


Автор: Anatoly Zhigljavsky; Antanas ?ilinskas
Название: Stochastic Global Optimization
ISBN: 1441944850 ISBN-13(EAN): 9781441944856
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book presents the main methodological and theoretical developments in stochastic global optimization. The extensive text is divided into four chapters; some of the topics include an introduction to global random search, statistical inference, several associated random search algorithms, and various approaches to statistical models.

Stochastic Modeling and Optimization

Автор: David D. Yao; Hanqin Zhang; Xun Yu Zhou
Название: Stochastic Modeling and Optimization
ISBN: 1441930655 ISBN-13(EAN): 9781441930651
Издательство: Springer
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Цена: 14673.00 р.
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Описание: This books covers the broad range of research in stochastic models and optimization. Applications presented include networks, financial engineering, production planning, and supply chain management. Each contribution is aimed at graduate students working in operations research, probability, and statistics.

Stochastic Optimization and Economic Models

Автор: Jati Sengupta
Название: Stochastic Optimization and Economic Models
ISBN: 9048184266 ISBN-13(EAN): 9789048184262
Издательство: Springer
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Цена: 26546.00 р.
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Описание: Methods of ap- plied stochastic control using stochastic processes have now reached an exciti~g phase, where several disciplines like systems engineering, operations research and natural reso- ces interact along with the conventional fields such as mathematical economics, finance and control systems.

Stochastic Learning and Optimization

Автор: Xi-Ren Cao
Название: Stochastic Learning and Optimization
ISBN: 144194222X ISBN-13(EAN): 9781441942227
Издательство: Springer
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Цена: 25853.00 р.
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Описание: Performance optimization is vital in the design and operation of modern engineering systems. This book provides a unified framework based on a sensitivity point of view. It introduces new approaches and proposes new research topics.

Stochastic Optimization and Economic Models

Автор: Jati Sengupta
Название: Stochastic Optimization and Economic Models
ISBN: 902772301X ISBN-13(EAN): 9789027723017
Издательство: Springer
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Цена: 26546.00 р.
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Описание: Methods of ap- plied stochastic control using stochastic processes have now reached an exciti~g phase, where several disciplines like systems engineering, operations research and natural reso- ces interact along with the conventional fields such as mathematical economics, finance and control systems.

Stochastic Approximation and Optimization of Random Systems

Автор: L. Ljung; G. Pflug; H. Walk
Название: Stochastic Approximation and Optimization of Random Systems
ISBN: 3764327332 ISBN-13(EAN): 9783764327330
Издательство: Springer
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Цена: 3487.00 р.
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Описание: PHug) 7 Markovian stochastic optimization and stochastic approximation procedures 53 8 Asymptotic distributions 71 9 Stopping times 79 1O Applications of stochastic approximation methods 80 References for Part II 90 III Applications to adaptation algorithms (L.

Stochastic Optimization

Автор: Kurt Marti
Название: Stochastic Optimization
ISBN: 3540552251 ISBN-13(EAN): 9783540552253
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Papers from a meeting aiming to bring together scientists from stochastic programming and from engineering areas where mathematical programming models are common tools, for example, optimal structural design, power dispatch and acid rain management. Theory and method are both covered.

Stochastic Multi-Stage Optimization

Автор: Pierre Carpentier; Jean-Philippe Chancelier; Guy C
Название: Stochastic Multi-Stage Optimization
ISBN: 3319365150 ISBN-13(EAN): 9783319365152
Издательство: Springer
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Цена: 13275.00 р.
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Описание: The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the related discretization issues.

Stochastic Optimization in Insurance

Автор: Pablo Azcue; Nora Muler
Название: Stochastic Optimization in Insurance
ISBN: 1493909940 ISBN-13(EAN): 9781493909940
Издательство: Springer
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Цена: 6986.00 р.
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Описание: The main purpose of the book is to show how a viscosity approach can be used to tackle control problems in insurance.

Stochastic Hydrology and its Use in Water Resources Systems Simulation and Optimization

Автор: J.B. Marco; R. Harboe; J.D. Salas
Название: Stochastic Hydrology and its Use in Water Resources Systems Simulation and Optimization
ISBN: 940104743X ISBN-13(EAN): 9789401047432
Издательство: Springer
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Цена: 12157.00 р.
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Описание: Based on the NATO Advanced Study Institute, Peniscola, Spain, September 18-29, 1989

Advances in Stochastic and Deterministic Global Optimization

Автор: Panos M. Pardalos; Anatoly Zhigljavsky; Julius ?il
Название: Advances in Stochastic and Deterministic Global Optimization
ISBN: 3319299735 ISBN-13(EAN): 9783319299730
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Current research results in stochastic and deterministic global optimization including single and multiple objectives are explored and presented in this book by leading specialists from various fields. Contributions include applications to multidimensional data visualization, regression, survey calibration, inventory management, timetabling, chemical engineering, energy systems, and competitive facility location. Graduate students, researchers, and scientists in computer science, numerical analysis, optimization, and applied mathematics will be fascinated by the theoretical, computational, and application-oriented aspects of stochastic and deterministic global optimization explored in this book.

This volume is dedicated to the 70th birthday of Antanas ?ilinskas who is a leading world expert in global optimization. Professor ?ilinskas's research has concentrated on studying models for the objective function, the development and implementation of efficient algorithms for global optimization with single and multiple objectives, and application of algorithms for solving real-world practical problems.
Shape Optimization under Uncertainty from a Stochastic Programming Point of View

Автор: Harald Held
Название: Shape Optimization under Uncertainty from a Stochastic Programming Point of View
ISBN: 3834809098 ISBN-13(EAN): 9783834809094
Издательство: Springer
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Описание: Optimization problems whose constraints involve partial differential equations (PDEs) are relevant in many areas of technical, industrial, and economic app- cations. At the same time, they pose challenging mathematical research problems in numerical analysis and optimization. The present text is among the ?rst in the research literature addressing stochastic uncertainty in the context of PDE constrained optimization. The focus is on shape optimization for elastic bodies under stochastic loading. Analogies to ?nite dim- sional two-stage stochastic programming drive the treatment, with shapes taking the role of nonanticipative decisions.The main results concern level set-based s- chastic shape optimization with gradient methods involving shape and topological derivatives. The special structure of the elasticity PDE enables the numerical - lution of stochastic shape optimization problems with an arbitrary number of s- narios without increasing the computational effort signi?cantly. Both risk neutral and risk averse models are investigated. This monograph is based on a doctoral dissertation prepared during 2004-2008 at the Chair of Discrete Mathematics and Optimization in the Department of Ma- ematics of the University of Duisburg-Essen. The work was supported by the Deutsche Forschungsgemeinschaft (DFG) within the Priority Program "Optimi- tion with Partial Differential Equations." Rudiger Schultz Acknowledgments I owe a great deal to my supervisors, colleagues, and friends who have always supported, encouraged, andenlightenedmethroughtheirownresearch, comments, and questions.


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