[PDF] Risk And Uncertainty Reduction By Using Algebraic Inequalities eBook

Author : Michael T. Todinov
Publisher : CRC Press
Page : 142 pages
File Size : 36,27 MB
Release : 2020-06-02
Category : Technology & Engineering
ISBN : 100007644X

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This book covers the application of algebraic inequalities for reliability improvement and for uncertainty and risk reduction. It equips readers with powerful domain-independent methods for reducing risk based on algebraic inequalities and demonstrates the significant benefits derived from the application for risk and uncertainty reduction. Algebraic inequalities: • Provide a powerful reliability improvement, risk and uncertainty reduction method that transcends engineering and can be applied in various domains of human activity • Present an effective tool for dealing with deep uncertainty related to key reliability-critical parameters of systems and processes • Permit meaningful interpretations which link abstract inequalities with the real world • Offer a tool for determining tight bounds for the variation of risk-critical parameters and complying the design with these bounds to avoid failure • Allow optimising designs and processes by minimising the deviation of critical output parameters from their specified values and maximising their performance This book is primarily for engineering professionals and academic researchers in virtually all existing engineering disciplines.

Author : M. T. Todinov
Publisher :
Page : pages
File Size : 25,74 MB
Release : 2020
Category : Inequalities (Mathematics)
ISBN : 9780367504014

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"This book provides the reader with a domain-independent method for reducing risk through maximizing reliability, reducing epistemic uncertainty, reducing aleatory uncertainty, ranking the reliabilities of systems and processes, minimizing the risk of faulty assemblies, and ranking decision-making alternatives in the presence of deep uncertainty"--

Author : Michael Todinov
Publisher : CRC Press
Page : 154 pages
File Size : 17,98 MB
Release : 2021-10-13
Category : Technology & Engineering
ISBN : 100046895X

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This book introduces a new method based on algebraic inequalities for optimising engineering systems and processes, with applications in mechanical engineering, materials science, electrical engineering, reliability engineering, risk management and operational research. This book shows that the application potential of algebraic inequalities in engineering and technology is far-reaching and certainly not restricted to specifying design constraints. Algebraic inequalities can handle deep uncertainty associated with design variables and control parameters. With the method presented in this book, powerful new knowledge about systems and processes can be generated through meaningful interpretation of algebraic inequalities. This book demonstrates how the generated knowledge can be put into practice through covering the algebraic inequalities suitable for interpretation in different contexts and describing how to apply this knowledge to enhance system and process performance. Depending on the specific interpretation, knowledge, applicable to different systems from different application domains, can be generated from the same algebraic inequality. Furthermore, an important class of algebraic inequalities has been introduced that can be used for optimising systems and processes in any area of science and technology provided that the variables and the separate terms of the inequalities are additive quantities. With the presented various examples and solutions, this book will be of interest to engineers, students and researchers in the field of optimisation, engineering design, reliability engineering, risk management and operational research.

Author : Krishna B. Misra
Publisher : Springer Nature
Page : 811 pages
File Size : 14,35 MB
Release : 2020-11-16
Category : Technology & Engineering
ISBN : 3030557324

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This book considers all aspects of performability engineering, providing a holistic view of the activities associated with a product throughout its entire life cycle of the product, as well as the cost of minimizing the environmental impact at each stage, while maximizing the performance. Building on the editor's previous Handbook of Performability Engineering, it explains how performability engineering provides us with a framework to consider both dependability and sustainability in the optimal design of products, systems and services, and explores the role of performability in energy and waste minimization, raw material selection, increased production volume, and many other areas of engineering and production. The book discusses a range of new ideas, concepts, disciplines, and applications in performability, including smart manufacturing and Industry 4.0; cyber-physical systems and artificial intelligence; digital transformation of railways; and asset management. Given its broad scope, it will appeal to researchers, academics, industrial practitioners and postgraduate students involved in manufacturing, engineering, and system and product development.

Author : M. T. Todinov
Publisher :
Page : 0 pages
File Size : 24,82 MB
Release : 2021-10-13
Category : Technology & Engineering
ISBN : 9781003199830

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This book introduces a new method based on algebraic inequalities for optimising engineering systems and processes, with applications in mechanical engineering, materials science, electrical engineering, reliability engineering, risk management and operational research. This book shows that the application potential of algebraic inequalities in engineering and technology is far-reaching and certainly not restricted to specifying design constraints. Algebraic inequalities can handle deep uncertainty associated with design variables and control parameters. With the method presented in this book, powerful new knowledge about systems and processes can be generated through meaningful interpretation of algebraic inequalities. This book demonstrates how the generated knowledge can be put into practice through covering the algebraic inequalities suitable for interpretation in different contexts and describing how to apply this knowledge to enhance system and process performance. Depending on the specific interpretation, knowledge, applicable to different systems from different application domains, can be generated from the same algebraic inequality. Furthermore, an important class of algebraic inequalities has been introduced that can be used for optimising systems and processes in any area of science and technology provided that the variables and the separate terms of the inequalities are additive quantities. With the presented various examples and solutions, this book will be of interest to engineers, students and researchers in the field of optimisation, engineering design, reliability engineering, risk management and operational research.

Author : Joachim Gwinner
Publisher : CRC Press
Page : 334 pages
File Size : 21,81 MB
Release : 2021-12-21
Category : Mathematics
ISBN : 1351857665

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Uncertainty Quantification (UQ) is an emerging and extremely active research discipline which aims to quantitatively treat any uncertainty in applied models. The primary objective of Uncertainty Quantification in Variational Inequalities: Theory, Numerics, and Applications is to present a comprehensive treatment of UQ in variational inequalities and some of its generalizations emerging from various network, economic, and engineering models. Some of the developed techniques also apply to machine learning, neural networks, and related fields. Features First book on UQ in variational inequalities emerging from various network, economic, and engineering models Completely self-contained and lucid in style Aimed for a diverse audience including applied mathematicians, engineers, economists, and professionals from academia Includes the most recent developments on the subject which so far have only been available in the research literature

Author : Hayk Sedrakyan
Publisher : Springer
Page : 244 pages
File Size : 15,1 MB
Release : 2018-07-05
Category : Mathematics
ISBN : 3319778366

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This unique collection of new and classical problems provides full coverage of algebraic inequalities. Many of the exercises are presented with detailed author-prepared-solutions, developing creativity and an arsenal of new approaches for solving mathematical problems. Algebraic Inequalities can be considered a continuation of the book Geometric Inequalities: Methods of Proving by the authors. This book can serve teachers, high-school students, and mathematical competitors. It may also be used as supplemental reading, providing readers with new and classical methods for proving algebraic inequalities.

Author : Vladimir Koltchinskii
Publisher : Springer
Page : 259 pages
File Size : 23,51 MB
Release : 2011-07-29
Category : Mathematics
ISBN : 3642221475

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The purpose of these lecture notes is to provide an introduction to the general theory of empirical risk minimization with an emphasis on excess risk bounds and oracle inequalities in penalized problems. In recent years, there have been new developments in this area motivated by the study of new classes of methods in machine learning such as large margin classification methods (boosting, kernel machines). The main probabilistic tools involved in the analysis of these problems are concentration and deviation inequalities by Talagrand along with other methods of empirical processes theory (symmetrization inequalities, contraction inequality for Rademacher sums, entropy and generic chaining bounds). Sparse recovery based on l_1-type penalization and low rank matrix recovery based on the nuclear norm penalization are other active areas of research, where the main problems can be stated in the framework of penalized empirical risk minimization, and concentration inequalities and empirical processes tools have proved to be very useful.

Author : Baoding Liu
Publisher : Springer
Page : 263 pages
File Size : 47,35 MB
Release : 2007-09-14
Category : Technology & Engineering
ISBN : 3540731652

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This book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory. The purpose is to equip the readers with an axiomatic approach to deal with uncertainty. For this new edition the entire text has been totally rewritten. The chapters on chance theory and uncertainty theory are completely new. Mathematicians, researchers, engineers, designers, and students will find this work a stimulating and useful reference.

Author : Mykel J. Kochenderfer
Publisher : MIT Press
Page : 350 pages
File Size : 45,16 MB
Release : 2015-07-24
Category : Computers
ISBN : 0262331713

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An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.