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Stochastic Methods for Estimation and Problem Solving in Engineering

Author: Kadry, Seifedine

Publisher: IGI Global

Published: 2018-03-02

Total Pages: 275

ISBN-13: 1522550461

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 Processes

Author: Kaddour Najim

Publisher: Elsevier

Published: 2004-07-01

Total Pages: 345

ISBN-13: 008051779X

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A ‘stochastic’ process is a ‘random’ or ‘conjectural’ process, and this book is concerned with applied probability and statistics. Whilst maintaining the mathematical rigour this subject requires, it addresses topics of interest to engineers, such as problems in modelling, control, reliability maintenance, data analysis and engineering involvement with insurance.This book deals with the tools and techniques used in the stochastic process – estimation, optimisation and recursive logarithms – in a form accessible to engineers and which can also be applied to Matlab. Amongst the themes covered in the chapters are mathematical expectation arising from increasing information patterns, the estimation of probability distribution, the treatment of distribution of real random phenomena (in engineering, economics, biology and medicine etc), and expectation maximisation. The latter part of the book considers optimization algorithms, which can be used, for example, to help in the better utilization of resources, and stochastic approximation algorithms, which can provide prototype models in many practical applications. * An engineering approach to applied probabilities and statistics * Presents examples related to practical engineering applications, such as reliability, randomness and use of resources* Readers with varying interests and mathematical backgrounds will find this book accessible

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.

Stochastic Systems for Engineers

Author: John A. Borrie

Publisher:

Published: 1992

Total Pages: 308

ISBN-13:

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A self-contained introduction to stochastic systems and an ordered presentation of techniques for computer modelling, filtering and control of these systems. The subject is developed with definition, formulae and explanations but without detailed mathematical proofs.

Stochastic Methods in Engineering

Author: I. St Doltsinis

Publisher: WIT Press

Published: 2012

Total Pages: 379

ISBN-13: 1845646266

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The increasing industrial demand for reliable quantification and management of uncertainty in product performance forces engineers to employ probabilistic models in analysis and design, a fact that has occasioned considerable research and development activities in the field. Notes on Stochastics eventually address the topic of computational stochastic mechanics. The single volume uniquely presents tutorials on essential probabilistics and statistics, recent finite element methods for stochastic analysis by Taylor series expansion as well as Monte Carlo simulation techniques. Design improvement and robust optimisation represent key issues as does reliability assessment. The subject is developed for solids and structures of elastic and elasto-plastic material, large displacements and material deformation processes; principles are transferable to various disciplines. A chapter is devoted to the statistical comparison of systems exhibiting random scatter. Where appropriate examples illustrate the theory, problems to solve appear instructive; applications are presented with relevance to engineering practice. The book, emanating from a university course, includes research and development in the field of computational stochastic analysis and optimization. It is intended for advanced students in engineering and for professionals who wish to extend their knowledge and skills in computational mechanics to the domain of stochastics. Contents: Introduction, Randomness, Structural analysis by Taylor series expansion, Design optimization, Robustness, Monte Carlo techniques for system response and design improvement, Reliability, Time variant phenomena, Material deformation processes, Analysis and comparison of data sets, Probability distribution of test functions.

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 and Filtering Theory

Author: Andrew H. Jazwinski

Publisher: Courier Corporation

Published: 2013-04-15

Total Pages: 404

ISBN-13: 0486318192

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This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well. Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probability theory and stochastic processes, the author introduces and defines the problems of filtering, prediction, and smoothing. He presents the mathematical solutions to nonlinear filtering problems, and he specializes the nonlinear theory to linear problems. The final chapters deal with applications, addressing the development of approximate nonlinear filters, and presenting a critical analysis of their performance.

Eco-Friendly Energy Processes and Technologies for Achieving Sustainable Development

Author: Danish, Mir Sayed Shah

Publisher: IGI Global

Published: 2020-10-23

Total Pages: 340

ISBN-13: 1799849163

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Rapid changes in technology and lifestyle have led to a dramatic increase in energy demand. Growing energy demand is the main cause of environmental pollution, but the efficient use of renewable resources and technologies for residential, commercial, industrial, and agricultural sectors offers the opportunity to diminish energy dependence, ensure efficiency and reliability, reduce pollutant emissions, and buoy national economies. Eco-friendly energy processes are the key to long-term sustainability. Eco-Friendly Energy Processes and Technologies for Achieving Sustainable Development is a collection of innovative research that identifies sustainability pillars such as environmental, technical, social, institutional, and economic disciplines and explores the longevity of these disciplines through a resource-oriented approach. Featuring coverage of a broad range of topics including environmental policy, corporate accountability, and urban planning, this book is ideally designed for policymakers, urban planners, engineers, advocates, researchers, academicians, and students.

Applying Integration Techniques and Methods in Distributed Systems and Technologies

Author: Kecskemeti, Gabor

Publisher: IGI Global

Published: 2019-04-12

Total Pages: 351

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.

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.