Описание: This concise and elementary introduction to stochastic control and mathematical modelling is designed for researchers in stochastic control theory studying its application in mathematical economics, and for interested economics researchers. Also suitable for graduate students in applied mathematics, mathematical economics, and non-linear PDE theory.
Описание: This monograph is devoted to random walk based stochastic algorithms for solving high-dimensional boundary value problems of mathematical physics and chemistry. It includes Monte Carlo methods where the random walks live not only on the boundary, but also inside the domain. A variety of examples from capacitance calculations to electron dynamics in semiconductors are discussed to illustrate the viability of the approach.The book is written for mathematicians who work in the field of partial differential and integral equations, physicists and engineers dealing with computational methods and applied probability, for students and postgraduates studying mathematical physics and numerical mathematics. Contents: IntroductionRandom walk algorithms for solving integral equationsRandom walk-on-boundary algorithms for the Laplace equationWalk-on-boundary algorithms for the heat equationSpatial problems of elasticityVariants of the random walk on boundary for solving stationary potential problemsSplitting and survival probabilities in random walk methods and applicationsA random WOS-based KMC method for electron-hole recombinationsMonte Carlo methods for computing macromolecules properties and solving related problemsBibliography
Автор: Flavio Canavero Название: Uncertainty Modeling for Engineering Applications ISBN: 3030048691 ISBN-13(EAN): 9783030048693 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides an overview of state-of-the-art uncertainty quantification (UQ) methodologies and applications, and covers a wide range of current research, future challenges and applications in various domains, such as aerospace and mechanical applications, structure health and seismic hazard, electromagnetic energy (its impact on systems and humans) and global environmental state change. Written by leading international experts from different fields, the book demonstrates the unifying property of UQ theme that can be profitably adopted to solve problems of different domains. The collection in one place of different methodologies for different applications has the great value of stimulating the cross-fertilization and alleviate the language barrier among areas sharing a common background of mathematical modeling for problem solution. The book is designed for researchers, professionals and graduate students interested in quantitatively assessing the effects of uncertainties in their fields of application. The contents build upon the workshop “Uncertainty Modeling for Engineering Applications” (UMEMA 2017), held in Torino, Italy in November 2017.
Автор: George Yin; Qing Zhang Название: Modeling, Stochastic Control, Optimization, and Applications ISBN: 3030254976 ISBN-13(EAN): 9783030254971 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume collects papers, based on invited talks given at the IMA workshop in Modeling, Stochastic Control, Optimization, and Related Applications, held at the Institute for Mathematics and Its Applications, University of Minnesota, during May and June, 2018. There were four week-long workshops during the conference. They are (1) stochastic control, computation methods, and applications, (2) queueing theory and networked systems, (3) ecological and biological applications, and (4) finance and economics applications. For broader impacts, researchers from different fields covering both theoretically oriented and application intensive areas were invited to participate in the conference. It brought together researchers from multi-disciplinary communities in applied mathematics, applied probability, engineering, biology, ecology, and networked science, to review, and substantially update most recent progress. As an archive, this volume presents some of the highlights of the workshops, and collect papers covering a broad range of topics.
Автор: Yin George, Zhang Qing Название: Modeling, Stochastic Control, Optimization, and Applications ISBN: 303025500X ISBN-13(EAN): 9783030255008 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume collects papers, based on invited talks given at the IMA workshop in Modeling, Stochastic Control, Optimization, and Related Applications, held at the Institute for Mathematics and Its Applications, University of Minnesota, during May and June, 2018.
Автор: J.S. Byrnes; Kathryn A. Hargreaves; Karl Berry Название: Probabilistic and Stochastic Methods in Analysis, with Applications ISBN: 0792318048 ISBN-13(EAN): 9780792318040 Издательство: Springer Рейтинг: Цена: 65685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Contains three expositions on wavelets, frames and their applications. This book includes the relation between probability and partial differential equations, including probabilistic representations of solutions to elliptic and parabolic PDEs.
Автор: Kurt Marti; Peter Kall Название: Stochastic Programming Methods and Technical Applications ISBN: 3540639241 ISBN-13(EAN): 9783540639244 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Optimization problems arising in practice usually contain several random parameters. The original problem with random parameters must be replaced by an appropriate deterministic substitute problem, and efficient numerical solution or approximation techniques have to be developed for those problems.
Автор: J.S. Byrnes; Kathryn A. Hargreaves; Karl Berry Название: Probabilistic and Stochastic Methods in Analysis, with Applications ISBN: 9401052395 ISBN-13(EAN): 9789401052399 Издательство: Springer Рейтинг: Цена: 41925.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Proceedings of the NATO Advanced Study Institute, Il Ciocco, Italy, July 14-27, 1991
Описание: Stochastic dominance is a fundamental concept used heavily in various fields of science such as economics, finance, insurance, medicine, and statistics. This book examines stochastic dominance in a unified framework, focusing on inferential methods and foundations. It will appeal to graduate students, academic researchers, and professionals.
Описание: This book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems and to schedule maintenance and logistics plans.
Автор: Klein Haneveld Willem K., Van Der Vlerk Maarten H., Romeijnders Ward Название: Stochastic Programming: Modeling Decision Problems Under Uncertainty ISBN: 3030292215 ISBN-13(EAN): 9783030292218 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides an essential introduction to Stochastic Programming, especially intended for graduate students. Several models for this problem are presented, including the main ones used in Stochastic Programming: recourse models and chance constraint models.
Описание: 1. Optimal Control under Stochastic Uncertainty.- 2. Stochastic Optimization of Regulators.- 3. Optimal Open-Loop Control of Dynamic Systems under Stochastic Uncertainty.- 4. Construction of feedback control by means of homotopy methods.- 5. Constructions of Limit State Functions.- 6. Random Search Procedures for Global Optimization.- 7. Controlled Random Search under Uncertainty.- 8. Controlled Random Search Procedures for Global Optimization.- 9. Mathematical Model of Random Search Methods and Elementary Properties.- 10. Special Random Search Methods.- 11. Accessibility Theorems.- 12. Convergence Theorems.- 13. Convergence of Stationary Random Search Methods for Positive Success Probability.- 14. Random Search Methods of convergence order U(n-").- 15. Random Search Methods with a Linear Rate of Convergence.- 16. Success/Failure-driven Random Direction Procedures.- 17. Hybrid Methods.- 18. Solving optimization problems under stochastic uncertainty by Random Search Methods(RSM).
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