Uncertainty Modeling
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Uncertainty Modeling For Engineering Applications
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Author : Flavio Canavero
language : en
Publisher: Springer
Release Date : 2018-12-29
Uncertainty Modeling For Engineering Applications written by Flavio Canavero and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-29 with Technology & Engineering categories.
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.
Applied Research In Uncertainty Modeling And Analysis
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Author : Bilal M. Ayyub
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-29
Applied Research In Uncertainty Modeling And Analysis written by Bilal M. Ayyub and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-29 with Business & Economics categories.
The application areas of uncertainty are numerous and diverse, including all fields of engineering, computer science, systems control and finance. Determining appropriate ways and methods of dealing with uncertainty has been a constant challenge. The theme for this book is better understanding and the application of uncertainty theories. This book, with invited chapters, deals with the uncertainty phenomena in diverse fields. The book is an outgrowth of the Fourth International Symposium on Uncertainty Modeling and Analysis (ISUMA), which was held at the center of Adult Education, College Park, Maryland, in September 2003. All of the chapters have been carefully edited, following a review process in which the editorial committee scrutinized each chapter. The contents of the book are reported in twenty-three chapters, covering more than . . ... pages. This book is divided into six main sections. Part I (Chapters 1-4) presents the philosophical and theoretical foundation of uncertainty, new computational directions in neural networks, and some theoretical foundation of fuzzy systems. Part I1 (Chapters 5-8) reports on biomedical and chemical engineering applications. The sections looks at noise reduction techniques using hidden Markov models, evaluation of biomedical signals using neural networks, and changes in medical image detection using Markov Random Field and Mean Field theory. One of the chapters reports on optimization in chemical engineering processes.
Dynamics Under Uncertainty
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Author : Dragan Pamucar
language : en
Publisher: MDPI
Release Date : 2021-09-08
Dynamics Under Uncertainty written by Dragan Pamucar and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-08 with Computers categories.
The dynamics of systems have proven to be very powerful tools in understanding the behavior of different natural phenomena throughout the last two centuries. However, the attributes of natural systems are observed to deviate from their classical states due to the effect of different types of uncertainties. Actually, randomness and impreciseness are the two major sources of uncertainties in natural systems. Randomness is modeled by different stochastic processes and impreciseness could be modeled by fuzzy sets, rough sets, Dempster–Shafer theory, etc.
Modeling Uncertainty
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Author : Moshe Dror
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-01-31
Modeling Uncertainty written by Moshe Dror and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-01-31 with Business & Economics categories.
Writing in honour of Sid Yakowitz, 50 internationally known scholars have collectively contributed 30 papers on modelling uncertainty to this volume. These include papers with a theoretical emphasis and others that focus on applications.
Uncertainty Modeling And Analysis In Engineering And The Sciences
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Author : Bilal M. Ayyub
language : en
Publisher: CRC Press
Release Date : 2006-05-25
Uncertainty Modeling And Analysis In Engineering And The Sciences written by Bilal M. Ayyub and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-25 with Business & Economics categories.
Engineers and scientists often need to solve complex problems with incomplete information resources, necessitating a proper treatment of uncertainty and a reliance on expert opinions. Uncertainty Modeling and Analysis in Engineering and the Sciences prepares current and future analysts and practitioners to understand the fundamentals of knowledge a
Supply Chain Analytics
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Author : Işık Biçer
language : en
Publisher: Springer Nature
Release Date : 2023-06-27
Supply Chain Analytics written by Işık Biçer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-27 with Business & Economics categories.
This textbook offers a detailed account of analytical models used to solve complex supply chain problems. It introduces a unique risk analysis framework that helps the reader understand the sources of uncertainties and use appropriate models to improve decisions in supply chains. This framework illustrates the complete supply chain for a product and demonstrates the supply chain's exposure to demand, supply, inventory, and financial risks. Step by step, this book provides a detailed examination of analytical methods that optimize operational decisions under different types of uncertainty. It discusses stochastic inventory models, introduces uncertainty modeling methods, and explains methods for managing uncertainty. To help readers deepen their understanding, it includes access to various supplementary material including an online interactive tool in Python. This book is intended for undergraduate and graduate students of supply chain management with a focus on supply chain analytics. It also prepares practitioners to make better decisions in this field.
Uncertainty Modelling And Analysis
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Author : Bilal M. Ayyub
language : en
Publisher: Elsevier Publishing Company
Release Date : 1994
Uncertainty Modelling And Analysis written by Bilal M. Ayyub and has been published by Elsevier Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Computers categories.
Vital information on machine intelligence and pattern recognition is provided by this publication. In particular, the 31 papers discuss the ways in which uncertainty modelling and analysis are becoming an integral part of system definition and modelling in many fields. Contributions are sourced from an international base of researchers, scientists and engineers working on theoretical developments and diversified applications in engineering systems. The book is divided into two main parts. The first, Uncertainty Models and Measures, includes chapters on theoretical studies and developments carried out on uncertainty (including cognitive uncertainty and how it relates to information and intelligence), information, fuzzy logic, expert systems and neural networks. There are also chapters on modelling uncertainty in the reliability assessment of complex systems, linguistic connectives, the principle of maximum buoyancy, uncertain evidence, inductive learning, convex modelling, new uncertainty measures and information and uncertainty.The larger second part, Applications to Engineering Systems, contains application-oriented studies in fields related to civil, electrical, energy and general engineering systems. The papers cover studies on general uncertainty types in structural engineering, bridges, transmission structures, structural reliability, structural identification, system life cycle analysis, control, construction activities, decision analysis, signal detection, risk management, product quality, military command and control, data bases, long-term projections and predictions and assessment of insurance indices.The book conveys the excitement, advances and promises that all these fields offer to our expanding information-based technological society. It also hopes to stimulate the interest of other researchers around the world who are facing the challenge of new theoretical studies and innovative technological changes.
Uncertainty Modeling With Applications To Multidimensional Civil Engineering Systems
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Author : Ove Ditlevsen
language : en
Publisher:
Release Date : 1981
Uncertainty Modeling With Applications To Multidimensional Civil Engineering Systems written by Ove Ditlevsen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1981 with Mathematics categories.
Uncertainty Modeling And Decision Making In Geotechnics
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Author : Kok-Kwang Phoon
language : en
Publisher: CRC Press
Release Date : 2023-12-11
Uncertainty Modeling And Decision Making In Geotechnics written by Kok-Kwang Phoon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-11 with Technology & Engineering categories.
Uncertainty, Modeling, and Decision Making in Geotechnics shows how uncertainty quantification and numerical modeling can complement each other to enhance decision-making in geotechnical practice, filling a critical gap in guiding practitioners to address uncertainties directly. The book helps practitioners acquire a working knowledge of geotechnical risk and reliability methods and guides them to use these methods wisely in conjunction with data and numerical modeling. In particular, it provides guidance on the selection of realistic statistics and a cost-effective, accessible method to address different design objectives, and for different problem settings, and illustrates the value of this to decision-making using realistic examples. Bringing together statistical characterization, reliability analysis, reliability-based design, probabilistic inverse analysis, and physical insights drawn from case studies, this reference guide from an international team of experts offers an excellent resource for state-of-the-practice uncertainty-informed geotechnical design for specialist practitioners and the research community.
Modeling Uncertainty With Fuzzy Logic
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Author : Asli Celikyilmaz
language : en
Publisher: Springer
Release Date : 2009-04-01
Modeling Uncertainty With Fuzzy Logic written by Asli Celikyilmaz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-01 with Computers categories.
The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron stock? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, “The only satisfactory description of uncertainty is probability.