Stochastic Methods for Estimation and Problem Solving in Engineering
Stochastic Methods for Estimation and Problem Solving in Engineering

Author: Kadry, Seifedine

Publisher: IGI Global

Published: 2018-03-02

Total Pages: 291

ISBN-13: 1522550461

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Utilizing mathematical algorithms is an important aspect of recreating real-world problems in order to make important decisions. By generating a randomized algorithm that produces statistical patterns, it becomes easier to find solutions to countless situations. Stochastic Methods for Estimation and Problem Solving in Engineering provides emerging research on the role of random probability systems in mathematical models used in various fields of research. While highlighting topics, such as random probability distribution, linear systems, and transport profiling, this book explores the use and behavior of uncertain probability methods in business and science. This book is an important resource for engineers, researchers, students, professionals, and practitioners seeking current research on the challenges and opportunities of non-deterministic probability models.

Stochastic Optimization Methods
Stochastic Optimization Methods

Author: Kurt Marti

Publisher: Springer

Published: 2015-02-21

Total Pages: 389

ISBN-13: 3662462141

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This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the probabilities and expectations involved, the book also shows how to apply approximative solution techniques. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures and differentiation formulas for probabilities and expectations. In the third edition, this book further develops stochastic optimization methods. In particular, it now shows how to apply stochastic optimization methods to the approximate solution of important concrete problems arising in engineering, economics and operations research.

Stochastic Processes, Estimation, and Control
Stochastic Processes, Estimation, and Control

Author: Jason L. Speyer

Publisher: SIAM

Published: 2008-11-06

Total Pages: 391

ISBN-13: 0898716551

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The authors provide a comprehensive treatment of stochastic systems from the foundations of probability to stochastic optimal control. The book covers discrete- and continuous-time stochastic dynamic systems leading to the derivation of the Kalman filter, its properties, and its relation to the frequency domain Wiener filter aswell as the dynamic programming derivation of the linear quadratic Gaussian (LQG) and the linear exponential Gaussian (LEG) controllers and their relation to HÝsubscript 2¨ and HÝsubscript Ýinfinity¨¨ controllers and system robustness. This book is suitable for first-year graduate students in electrical, mechanical, chemical, and aerospace engineering specializing in systems and control. Students in computer science, economics, and possibly business will also find it useful.

Introduction to Stochastic Search and Optimization
Introduction to Stochastic Search and Optimization

Author: James C. Spall

Publisher: John Wiley & Sons

Published: 2005-03-11

Total Pages: 620

ISBN-13: 0471441902

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* Unique in its survey of the range of topics. * Contains a strong, interdisciplinary format that will appeal to both students and researchers. * Features exercises and web links to software and data sets.

Applying Integration Techniques and Methods in Distributed Systems and Technologies
Applying Integration Techniques and Methods in Distributed Systems and Technologies

Author: Kecskemeti, Gabor

Publisher: IGI Global

Published: 2019-04-12

Total Pages: 368

ISBN-13: 1522582967

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Distributed systems intertwine with our everyday lives. The benefits and current shortcomings of the underpinning technologies are experienced by a wide range of people and their smart devices. With the rise of large-scale IoT and similar distributed systems, cloud bursting technologies, and partial outsourcing solutions, private entities are encouraged to increase their efficiency and offer unparalleled availability and reliability to their users. Applying Integration Techniques and Methods in Distributed Systems is a critical scholarly publication that defines the current state of distributed systems, determines further goals, and presents architectures and service frameworks to achieve highly integrated distributed systems and presents solutions to integration and efficient management challenges faced by current and future distributed systems. Highlighting topics such as multimedia, programming languages, and smart environments, this book is ideal for system administrators, integrators, designers, developers, researchers, and academicians.

Applied Stochastic Differential Equations
Applied Stochastic Differential Equations

Author: Simo Särkkä

Publisher: Cambridge University Press

Published: 2019-05-02

Total Pages: 327

ISBN-13: 1316510085

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With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.

Stochastic Approximation and Recursive Estimation
Stochastic Approximation and Recursive Estimation

Author: M. B. Nevel'son

Publisher: American Mathematical Soc.

Published: 1976-10-01

Total Pages: 252

ISBN-13: 9780821809068

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This book is devoted to sequential methods of solving a class of problems to which belongs, for example, the problem of finding a maximum point of a function if each measured value of this function contains a random error. Some basic procedures of stochastic approximation are investigated from a single point of view, namely the theory of Markov processes and martingales. Examples are considered of applications of the theorems to some problems of estimation theory, educational theory and control theory, and also to some problems of information transmission in the presence of inverse feedback.

Research Directions in Computational Mechanics
Research Directions in Computational Mechanics

Author: National Research Council

Publisher: National Academies Press

Published: 1991-02-01

Total Pages: 145

ISBN-13: 0309046483

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Computational mechanics is a scientific discipline that marries physics, computers, and mathematics to emulate natural physical phenomena. It is a technology that allows scientists to study and predict the performance of various productsâ€"important for research and development in the industrialized world. This book describes current trends and future research directions in computational mechanics in areas where gaps exist in current knowledge and where major advances are crucial to continued technological developments in the United States.

Emerging Applications and Implementations of Metal-Organic Frameworks
Emerging Applications and Implementations of Metal-Organic Frameworks

Author: Elsaeed, Shimaa Mohamed

Publisher: IGI Global

Published: 2021-03-18

Total Pages: 254

ISBN-13: 1799847616

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Metal-organic frameworks (MOFs) are some of the most discussed materials of the last decade. Their extraordinary porosity and functionality from metals and organic linkers make them one of the most promising materials for a vast array of applications. The easy tunability of their pore size and shape from the micro- to meso-scale by changing the connectivity of the inorganic moiety and the nature of the organic linkers makes these materials special. Moreover, by combining with other suitable materials, the properties of MOFs can be improved further for enhanced functionality/stability, ease of preparation, and selectivity of operation. Emerging Applications and Implementations of Metal-Organic Frameworks combines the latest empirical research findings with relevant theoretical frameworks in this area in order to improve the reader’s understanding of MOFs and their different applications in areas that include drug delivery, heavy metal removal from water, and gas storage. The design and synthesis of MOFs are also investigated along with the preparation of composites of MOFs. While covering applications that include water defluoridation, rechargeable batteries, and pharmaceutically adapted drug delivery systems, the book’s target audience is comprised of professionals, researchers, academicians, and students working in the field of physical and polymer chemistry, physics, engineering science, and environmental science.