Описание: A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.
Автор: Bass Название: Probabilistic Techniques in Analysis ISBN: 0387943870 ISBN-13(EAN): 9780387943879 Издательство: Springer Рейтинг: Цена: 8982 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Exploring the use of techniques drawn from probability research to tackle problems in mathematical analysis, this study includes discussion of the construction of the Martin boundary, Dahlberg`s Theorem, probabilistic proofs of the boundary Harnack principle, and much more.
Описание: This complete resource on the theory and applications of reliability engineering, probabilistic models and risk analysis consolidates all the latest research, presenting the most up-to-date developments in this field.
Автор: Cooper, George R.; McGillem, Clare D. Название: Probabilistic Methods of Signal and System Analysis ISBN: 0195123549 ISBN-13(EAN): 9780195123548 Издательство: Oxford Academ Рейтинг: Цена: 20411 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Originally published in 1971, this text is intended for signals and systems courses which emphasize probability. It provides an introduction to probability theory, statistics, random processes and the analysis of systems with random inputs. This edition has been updated and uses Matlab.
Описание: This unique book proposes a uniform logic and probabilistic (LP) approach to risk estimation and analysis in engineering and economics. It includes clear definitions and notations, revised chapters, an extended list of references, and a new subject index.
Автор: Ellery Eells Название: Probabilistic Causality ISBN: 0521061326 ISBN-13(EAN): 9780521061322 Издательство: Cambridge Academ Рейтинг: Цена: 5061 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this important first book in the series Cambridge Studies in Probability, Induction and Decision Theory, Ellery Eells explores and refines current philosophical conceptions of probabilistic causality. In a probabilistic theory of causation, causes increase the probability of their effects rather than necessitate their effects in the ways traditional deterministic theories have specified. Philosophical interest in this subject arises from attempts to understand population sciences as well as indeterminism in physics. Taking into account issues involving spurious correlation, probabilistic causal interaction, disjunctive causal factors, and temporal ideas, Professor Eells advances the analysis of what it is for one factor to be a positive causal factor for another. A salient feature of the book is a new theory of token level probabilistic causation in which the evolution of the probability of a later event from an earlier event is central. This will be a book of crucial significance to philosophers of science and metaphysicians; it will also prove stimulating to many economists, psychologists, and physicists.
Описание: The lectures concentrate on some old and new relations between quasiderivatives of solutions to Ito stochastic equations and interior smoothness of harmonic functions associated with degenerate elliptic equations. Recent progress in the case of constant coefficients is discussed in full detail.
Автор: Griffiths D. V., Fenton G. A. Название: Probabilistic Methods in Geotechnical Engineering ISBN: 3211733655 ISBN-13(EAN): 9783211733653 Издательство: Springer Рейтинг: Цена: 13672 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Soils and rocks are among the most variable of all engineering materials, and as such are highly amenable to a probabilistic treatment. The application of statistical and probabilistic concepts to geotechnical analysis is a rapidly growing area of interest for both academics and practitioners. The book is therefore aimed at students, researchers, and practitioners of geotechnical engineering who wish to keep abreast of developments in this evolving field of study. The course content and will assume no more that an introductory understanding of probability and statistics on the part of the course participants.The main objective is to present a state-of-the-art training on probabilistic techniques applied to geotechnical engineering in relation to both theory and practice. Including:(a) discussion of potential benefits of probabilistic approaches as opposed to the classical вЂњFactor of SafetyвЂќ methods, to review sources of uncertainty in geotechnical analysis and to introduce methods of LRFD and reliability concepts in Eurocode 7,(b) review of relevant statistical theories needed to develop the methodologies and interpret the results of probabilistic analysis,(c) examples of established probabilistic methods of analysis in geotechnical engineering, such as the First Order Second Moment (FOSM) method, the Point Estimate Method (PEM), the First and Second Order Reliability Methods (FORM SORM) and Random Set (RS) theory,(d) description of numerical methods of probabilistic analysis based on the finite element method, such as the Stochastic Finite Element Method (SFEM) and recent developments on the Random Finite Element Method (RFEM),(e) practical examples and case histories of probabilistic applications in geotechnical engineering.
Описание: In recent years considerable progress has been made in the area of probabilistic graphical models, in particular Bayesian networks and influence diagrams. Probabilistic graphical models have become mainstream in the area of uncertainty in artificial intelligence;contributions to the area are coming from computer science, mathematics, statistics and engineering.This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.
Описание: Fixed point theory in probabilistic metric spaces can be considered as a part of Probabilistic Analysis, which is a very dynamic area of mathematical research. A primary aim of this monograph is to stimulate interest among scientists and students in this fascinating field. The text is self-contained for a reader with a modest knowledge of the metric fixed point theory. Several themes run through this book. The first is the theory of triangular norms (t-norms), which is closely related to fixed point theory in probabilistic metric spaces. Its recent development has had a strong influence upon the fixed point theory in probabilistic metric spaces. In Chapter 1 some basic properties of t-norms are presented and several special classes of t-norms are investigated. Chapter 2 is an overview of some basic definitions and examples from the theory of probabilistic metric spaces. Chapters 3, 4, and 5 deal with some single-valued and multi-valued probabilistic versions of the Banach contraction principle. In Chapter 6, some basic results in locally convex topological vector spaces are used and applied to fixed point theory in vector spaces. Audience: The book will be of value to graduate students, researchers, and applied mathematicians working in nonlinear analysis and probabilistic metric spaces.
Описание: Examines uncertain systems in control engineering and general decision or optimization problems for which data is uncertain. This book describes theory and solution methods for probability-constrained and stochastic optimization problems. It is of interest to researchers, academics and postgraduates in control engineering and operations research.
Автор: Kramosil Ivan Название: Probabilistic Analysis of Belief Functions ISBN: 030646702X ISBN-13(EAN): 9780306467028 Издательство: Springer Рейтинг: Цена: 14629 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume is a highly theoretical and mathematical study analyzing the notion and theory of belief functions, also known as the Dempster-Shafer theory, from the point of view of the classical Kolmogorov axiomatic probability theory. In other terms, the theory of belief functions is taken as an interesting, non-traditional application of probability theory, and the standard methodology of probability theory, and measure theory in general, is applied in order to arrive at some new and perhaps interesting generalizations and results not accessible within the classical combinatorial framework of the theory of belief functions (Dempster-Shafer theory) over finite spaces. The relation to great systems and their theory seems to be very close and should become clear from the first two chapters of the book.
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