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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.

Soft computing. --- Cognitive computing --- Electronic data processing --- Computational intelligence --- Uncertainty (Information theory) --- Measure of uncertainty (Information theory) --- Shannon's measure of uncertainty --- System uncertainty --- Information measurement --- Probabilities --- Questions and answers

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Markov decision processes have become the de facto standard in modeling and solving sequential decision making problems under uncertainty. This book studies lifting Markov decision processes, reinforcement learning and dynamic programming to the first-order (or, relational) setting.

Decision making --- Sequential analysis. --- Adaptive control systems. --- Uncertainty (Information theory) --- Computer algorithms. --- Algorithms --- Measure of uncertainty (Information theory) --- Shannon's measure of uncertainty --- System uncertainty --- Information measurement --- Probabilities --- Questions and answers --- Self-adaptive control systems --- Artificial intelligence --- Feedback control systems --- Self-organizing systems --- Mathematical statistics --- Statistical decision --- Mathematical models. --- Sequential analysis --- Adaptive control systems --- Computer algorithms --- Mathematical models --- E-books

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"Dimensions of Uncertainty in Communication Engineering is a comprehensive and self-contained introduction to the problems of nonaleatory uncertainty and the mathematical tools needed to solve them. The book gathers together tools derived from statistics, information theory, moment theory, interval analysis and probability boxes, dependence bounds, nonadditive measures, and Dempster–Shafer theory. While the book is mainly devoted to communication engineering, the techniques described are also of interest to other application areas, and commonalities to these are often alluded to through a number of references to books and research papers. This is an ideal supplementary book for courses in wireless communications, providing techniques for addressing epistemic uncertainty, as well as an important resource for researchers and industry engineers. Students and researchers in other fields such as statistics, financial mathematics, and transport theory will gain an overview and understanding on these methods relevant to their field. Key Features: Uniquely brings together a variety of tools derived from statistics, information theory, moment theory, interval analysis and probability boxes, dependence bounds, nonadditive measures, and Dempster—Shafer theory. Focuses on the essentials of various, wide-ranging methods with references to journal articles where more detail can be found if required. Includes MIMO-related results throughout."--Provided by publisher.

Uncertainty (Information theory) --- Telecommunication. --- Electrical engineering. --- Computer engineering. --- Computers --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Information theory --- Telecommuting --- Measure of uncertainty (Information theory) --- Shannon's measure of uncertainty --- System uncertainty --- Information measurement --- Probabilities --- Questions and answers --- Electric engineering --- Engineering --- Design and construction --- Uncertainty (Information theory).

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This volume contains an extensive survey and critical examination of current views on the use of expert opinion in scientific inquiry and policy-making.

Philosophy of science --- Besluitvorming --- Besluitvormingsanalyse --- Besluitvormingsprocessen --- Deciding --- Decision analysis --- Decision making --- Decision processes --- Decision-making --- Décision [Prise de ] --- Décision [Théorie de la ] --- Indetermination (Theorie de l'information) --- Making decisions --- Management decisions --- Management--Beslissingen --- Management--Besluitvorming --- Management--Decision making --- Onzekerheid (Informatietheorie) --- Prise de décision --- Probabiliteit--Theorie --- Probabiliteitstheorie --- Probabilities --- Probabilité [Théorie de la ] --- Probabilités --- Théorie de la décision --- Uncertainty (Information theory) --- Waarschijnlijkheid--Theorie --- Waarschijnlijkheidstheorie --- Science --- Sciences --- Incertitude (Théorie de l'information) --- Methodology --- Philosophy --- Méthodologie --- Philosophie --- Decision making. --- Decision-making. --- Probabilities. --- Science. --- Science - Philosophy. --- Uncertainty (Information theory). --- Sciences - General --- Physical Sciences & Mathematics --- -Science --- -Uncertainty (Information theory) --- Decision (Psychology) --- Management --- Choice (Psychology) --- Problem solving --- Measure of uncertainty (Information theory) --- Shannon's measure of uncertainty --- System uncertainty --- Information measurement --- Questions and answers --- Natural science --- Science of science --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Methodology. --- Philosophy. --- Prise de décision --- Probabilités --- Incertitude (Théorie de l'information) --- Méthodologie --- Scientific method --- Normal science --- Logic, Symbolic and mathematical --- Science - Methodology.