Download or read book Dynamics under Uncertainty written by Dragan Pamucar and published by MDPI. This book was released on 2021-09-08 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Uncertainty in System Dynamics Models written by Jean-Pierre Pouplard and published by . This book was released on 1978 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dynamics Under Uncertainty Modeling Simulation and Complexity written by Dragan Pamučar and published by . This book was released on 2021 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book SYSTEM DYNAMICS Volume II written by Yaman Barlas and published by EOLSS Publications. This book was released on 2009-06-29 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: System Dynamics is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. The world is facing a wide range of increasingly complex, dynamic problems in the public and private arenas alike. System dynamics discipline is an attempt to address such dynamic, long-term policy problems. Applications cover a very wide spectrum, including national economic problems, supply chains, project management, educational problems, energy systems, sustainable development, politics, psychology, medical sciences, health care, and many other areas. This theme provides a comprehensive overview of system dynamics methodology, including its conceptual / philosophical framework, as well as the technical aspects of modeling and analysis. System dynamics can address the fundamental structural causes of the long-term dynamic contemporary socio-economic problems. Its "systems" perspective challenges the barriers that separate disciplines. The interdisciplinary and systemic approach of system dynamics could be critical in dealing with the increasingly complex problems of our modern world in this new century. These two volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.
Download or read book Nonlinear Dynamics and Statistics written by Alistair I. Mees and published by Springer Science & Business Media. This book was released on 2001-01-25 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the state of the art in nonlinear dynamical reconstruction theory. The chapters are based upon a workshop held at the Isaac Newton Institute, Cambridge University, UK, in late 1998. The book's chapters present theory and methods topics by leading researchers in applied and theoretical nonlinear dynamics, statistics, probability, and systems theory. Features and topics: * disentangling uncertainty and error: the predictability of nonlinear systems * achieving good nonlinear models * delay reconstructions: dynamics vs. statistics * introduction to Monte Carlo Methods for Bayesian Data Analysis * latest results in extracting dynamical behavior via Markov Models * data compression, dynamics and stationarity Professionals, researchers, and advanced graduates in nonlinear dynamics, probability, optimization, and systems theory will find the book a useful resource and guide to current developments in the subject.
Download or read book Model Selection Uncertainty and Dynamics Models written by and published by . This book was released on 2000 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Uncertainty Modeling in Vibration Control and Fuzzy Analysis of Structural Systems written by Bilal M. Ayyub and published by World Scientific. This book was released on 1997 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives an overview of the current state of uncertainty modeling in vibration, control, and fuzzy analysis of structural and mechanical systems. It is a coherent compendium written by leading experts and offers the reader a sampling of exciting research areas in several fast-growing branches in this field. Uncertainty modeling and analysis are becoming an integral part of system definition and modeling in many fields. The book consists of ten chapters that report the work of researchers, scientists and engineers on theoretical developments and diversified applications in engineering systems. They deal with modeling for vibration, control, and fuzzy analysis of structural and mechanical systems under uncertain conditions. The book designed for readers who are familiar with the fundamentals and wish to study a particular topic or use the book as an authoritative reference. It gives readers a sophisticated toolbox for tackling modeling problems in mechanical and structural systems in real-world situations. The book is part of a series on Stability, Vibration and Control of Structures, and provides vital information in these areas.
Download or read book Uncertainty written by Millett Granger Morgan and published by Cambridge University Press. This book was released on 1990 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: A risk analysis textbook which is intended as a basic text for students as well as a reference for practitioners and researchers. It provides a basis for policy analysis and draws upon a variety of case studies.
Download or read book Convex Models of Uncertainty in Applied Mechanics written by Y. Ben-Haim and published by Elsevier. This book was released on 2013-10-22 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recognition of the need to introduce the ideas of uncertainty in a wide variety of scientific fields today reflects in part some of the profound changes in science and engineering over the last decades. Nobody questions the ever-present need for a solid foundation in applied mechanics. Neither does anyone question nowadays the fundamental necessity to recognize that uncertainty exists, to learn to evaluate it rationally, and to incorporate it into design.This volume provides a timely and stimulating overview of the analysis of uncertainty in applied mechanics. It is not just one more rendition of the traditional treatment of the subject, nor is it intended to supplement existing structural engineering books. Its aim is to fill a gap in the existing professional literature by concentrating on the non-probabilistic model of uncertainty. It provides an alternative avenue for the analysis of uncertainty when only a limited amount of information is available. The first chapter briefly reviews probabilistic methods and discusses the sensitivity of the probability of failure to uncertain knowledge of the system. Chapter two discusses the mathematical background of convex modelling. In the remainder of the book, convex modelling is applied to various linear and nonlinear problems. Uncertain phenomena are represented throughout the book by convex sets, and this approach is referred to as convex modelling.This book is intended to inspire researchers in their goal towards further growth and development in this field.
Download or read book Exploratory Modeling and Analysis written by Buyung Agusdinata and published by . This book was released on 2008 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling Estimation and Control of Systems with Uncertainty written by G.B. DiMasi and published by Springer Science & Business Media. This book was released on 2013-03-12 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers that have been presented at the Conference on Modeling and Control of Uncertain Systems held in Sopron, Hungary on September 3-7, 1990, organised within the framework of the activities of the System and Decision Sciences Program of IIASA - the International Institute for Applied Systems Analysis. The importance of the subject has drawn the attention of researchers all over the world since several years. In fact, in most actual applications the knowledge about the system under investigation presents aspects of uncertainty due to measurement errors or poor understanding of the rele vant underlying mechanisms. For this reason models that take into account these intrinsic uncertainties have been used and techniques for the analysis of their behavior as well as for their estimation and control have been devel oped. The main ways to deal with uncertainty consist in its description by stochastic processes or in terms of set-valued dynamics and this volume col lects relevant contributions in both directions. However, in order to avoid undesirable distinctions between these approaches, but on the contrary to stress the unity of ideas, we decided to organize the papers according to the alphabetical order of their authors. We should like to take this opportunity to thank IIASA for supporting the Conference and the Hungarian National Member Organization for the kind hospitality in Sopron. Finally we would like to express our gratitude to Ms. Donna Huchthausen for her valuable secretarial assistance. Vienna, February 20, 1991 GIOVANNI B.
Download or read book Comparing Dynamic System Models with Additive Uncertainty written by Aditya Karumanchi and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the complexity of the operational design domain of Automated Driving Systems, the industry is trending towards the use of simulation-based methods for their verification and validation (V\&V), which rely on the use of models of the vehicles, sensors, vehicle environments, etc. Depending on the testing requirements, computational capabilities, modeling effort, and other such factors, these models can vary in fidelity. However, this variation in fidelity has an effect on the excitation of the control systems under test, and can therefore affect the results of the tests themselves. Moreover, since every model is an approximation of the actual physical system it represents, there is uncertainty associated with its output. Therefore, we need to be able to compare uncertain system models in order to understand the effect of model fidelity variation on test accuracy. The existing metrics such as Hankel Singular Values compare asymptotic behavior of the models, whereas simulation studies are over finite time. Although some of these metrics may be applied over finite time, they rely on hyper-parameters like weights on time or frequency. In this study, we propose an approach for computing a (pseudo)metric based on the literature for comparing the predictive performance of two models, called finite-time Kullback-Leibler (KL) rate. For any two general state space models with a general additive uncertainty, we first discuss an approach for propagating a general additive uncertainty (represented as a Gaussian Mixture Model (GMM) ) through a linear time-invariant system. We then apply this propagation approach to linear representations of nonlinear systems obtained through Dynamic Mode Decomposition (DMD). We illustrate this combined approach for the comparison of two lateral vehicle dynamics models over an obstacle avoidance maneuver to measure the effect of fidelity on the predictive performance of each model. We also apply this to a \vv problem, wherein we compare the application of the two vehicle dynamics models to reference vehicle trajectories. We see that the KL rate depends not only on the differences in the asymptotic spectral properties of each model, but also on the trajectory being simulated. Through these methods, we illustrate a process for comparing models of different fidelity over relevant trajectories. This enables us to understand which model is most appropriate for a particular scenario in a virtual test. We also show that the variation in the comparison metric can be connected to the phase space of the system. This enables us to use thresholds on the metric to decide when to switch between models of different fidelity.
Download or read book Model Validation and Uncertainty Quantification Volume 3 written by Zhu Mao and published by Springer Nature. This book was released on 2020-10-27 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020, the third volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Uncertainty Quantification in Material Models Uncertainty Propagation in Structural Dynamics Practical Applications of MVUQ Advances in Model Validation & Uncertainty Quantification: Model Updating Model Validation & Uncertainty Quantification: Industrial Applications Controlling Uncertainty Uncertainty in Early Stage Design Modeling of Musical Instruments Overview of Model Validation and Uncertainty
Download or read book Soft Numerical Computing in Uncertain Dynamic Systems written by Tofigh Allahviranloo and published by Academic Press. This book was released on 2020-08-19 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft Numerical Computing in Uncertain Dynamic Systems is intended for system specialists interested in dynamic systems that operate at different time scales. The book discusses several types of errors and their propagation, covering numerical methods—including convergence and consistence properties and characteristics—and proving of related theorems within the setting of soft computing. Several types of uncertainty representation like interval, fuzzy, type 2 fuzzy, granular, and combined uncertain sets are discussed in detail. The book can be used by engineering students in control and finite element fields, as well as all engineering, applied mathematics, economics, and computer science students. One of the important topics in applied science is dynamic systems and their applications. The authors develop these models and deliver solutions with the aid of numerical methods. Since they are inherently uncertain, soft computations are of high relevance here. This is the reason behind investigating soft numerical computing in dynamic systems. If these systems are involved with complex-uncertain data, they will be more practical and important. Real-life problems work with this type of data and most of them cannot be solved exactly and easily—sometimes they are impossible to solve. Clearly, all the numerical methods need to consider error of approximation. Other important applied topics involving uncertain dynamic systems include image processing and pattern recognition, which can benefit from uncertain dynamic systems as well. In fact, the main objective is to determine the coefficients of a matrix that acts as the frame in the image. One of the effective methods exhibiting high accuracy is to use finite differences to fill the cells of the matrix. Explores dynamic models, how time is fundamental to the structure of the model and data, and how a process unfolds Investigates the dynamic relationships between multiple components of a system in modeling using mathematical models and the concept of stability in uncertain environments Exposes readers to many soft numerical methods to simulate the solution function’s behavior
Download or read book Applied Research in Uncertainty Modeling and Analysis written by Bilal M. Ayyub and published by Springer Science & Business Media. This book was released on 2007-12-29 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Model Validation and Uncertainty Quantification Volume 3 written by H. Sezer Atamturktur and published by Springer Science & Business Media. This book was released on 2014-04-11 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: This third volume of eight from the IMAC - XXXII Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Linear Systems Substructure Modelling Adaptive Structures Experimental Techniques Analytical Methods Damage Detection Damping of Materials & Members Modal Parameter Identification Modal Testing Methods System Identification Active Control Modal Parameter Estimation Processing Modal Data
Download or read book Model Validation and Uncertainty Quantification Volume 3 written by Robert Barthorpe and published by Springer. This book was released on 2019-05-30 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics, 2019, the third volume of eight from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Inverse Problems and Uncertainty Quantification Controlling Uncertainty Validation of Models for Operating Environments Model Validation & Uncertainty Quantification: Decision Making Uncertainty Quantification in Structural Dynamics Uncertainty in Early Stage Design Computational and Uncertainty Quantification Tools
