الصفحة 3
الصفحة 3
Symbolic and quantitative approaches to reasoning with uncertainty ; 9th European Conference, ECSQARU 2007, Hammamet, Tunisia, October 31 - November 2, 2007, Proceedings
Coverage in the 78 revised full papers, presented together with three invited papers, includes Bayesian networks, graphical models, learning causal networks, planning, causality and independence, preference modeling and decision, argumentation systems, inconsistency handling, and uncertainty measures.
Symbolic and quantitative approaches to reasoning with uncertainty ; 8th European Conference, ECSQARU 2005, Barcelona, Spain, July 6-8, 2005, Proceedings
These are the proceedings of the 8th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2005, held in Barcelona (Spain), July 6-8, 2005.
Switching and learning in feedback systems : European Summer School on Multi-Agent Control, Maynooth, Ireland, September 8-10, 2003, Revised Lectures and Selected Papers
A central theme in the study of dynamic systems is the modelling and control of uncertain systems. While ‘uncertainty’ has long been a strong motivating factor behind many techniques developed in the modelling, control, statistics and mathematics communities, the past decade, in particular, has witnessed remarkable progress in this area with the emergence of a number of powerful new methods for both modelling and controlling uncertain dynamic systems. The specific objective of this book is to describe and review some of these exciting new approaches within a single volume. Our approach was to invite some of the leading researchers in this area to contribute to this book by submitting both tutorial papers on their speci?c area of research, and to submit more focussed research papers to document some of the latest results in the area. We feel that collecting some of the main results together in this manner is particularly important as many of the important ideas that emerged in the past decade were derived in a variety of academic disciplines.
Super-Flexibility for Knowledge Enterprises : A Toolkit for Dynamic Adaption
Living with uncertainty is an everyday reality for most business entities today. This is especially the case for knowledge-intensive enterprises, such as those in technology, financial services, biotechnology and telecommunications, where new innovations and shifting customer preferences can radically change competitive dynamics. The focus of the book is on how knowledge enterprises can harness uncertainty by becoming super-flexible. Based on over 20 years of field research and practical experience in Silicon Valley’s technology ecosystem, the authors present conceptual frameworks, illustrative examples and practical lessons for strategizing, organizing and managing knowledge-based enterprises in turbulent settings.
Studying Human Populations : An Advanced Course in Statistics
Studying Human Populations is a textbook for graduate students and research workers in social statistics and related subject areas. It follows a novel curriculum developed around the basic statistical activities of sampling, measurement and inference. Statistics is defined broadly as making decisions in the presence of uncertainty that arises as a consequence of limited resources available for collecting information. A connecting link of the presented methods is the perspective of missing information, catering for a diverse class of problems that include nonresponse, imperfect measurement and causal inference. In principle, any problem too complex for our limited analytical toolkit could be converted to a tractable problem if some additional information were available. Ingenuity is called for in declaring such (missing) information constructively, but the universe of problems that we can address is wide open, not limited by a discrete set of procedures.
Stochastic Orders
Stochastic ordering is a fundamental guide for decision making under uncertainty. It is also an essential tool in the study of structural properties of complex stochastic systems. This reference text presents a comprehensive coverage of the various notions of stochastic orderings, their closure properties, and their applications. Some of these orderings are routinely used in many applications in economics, finance, insurance, management science, operations research, statistics, and various other fields of study. And the value of the other notions of stochastic orderings still needs to be explored further.
Stochastic Optimization Methods ; 1st ed.
Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.
Stochastic Optimization Methods ; 2nd ed.
Optimization problems arising in practice involve random model parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures, differentiation formulas for probabilities and expectations.
Stochastic Dominance : Investment Decision Making under Uncertainty
Stochastic Dominance is devoted to investment decision-making under uncertainty. The book covers three basic approaches to this process: The stochastic dominance approach; the mean-variance approach; and the non-expected utility approach, focusing on prospect theory and its modified version, cumulative prospect theory. These approaches are discussed and compared in this book.
Statistics and the evaluation of evidence for forensic scientists
Provides the latest research and developments in the use of statistical techniques to evaluate and interpret evidence. Courts are increasingly aware of the importance of proper evidence assessment when there is an element of uncertainty. Because of the increasing availability of data, the role of statistical and probabilistic reasoning is gaining a higher profile in criminal cases.
Statistical Analysis of Environmental Space-Time Processes
This book provides a broad introduction to the fascinating subject of environmental space-time processes; addressing the role of uncertainty. Within that context, it covers a spectrum of technical matters from measurement to environmental epidemiology to risk assessment. It showcases non-stationary vector-valued processes, while treating stationarity as a special case.
Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018 ; Selected Papers from the ICOSAHOM Conference, London, UK, July 9-13, 2018
Features a selection of high-quality papers from the presentations at the International Conference on Spectral and High-Order Methods 2018, offering an overview of the depth and breadth of the activities within this important research area. The carefully reviewed papers provide a snapshot of the state of the art, while the extensive bibliography helps initiate new research directions.
Spatial Information Theory ; International Conference, COSIT 2005, Ellicottville, NY, USA, September 14-18, 2005, Proceedings
Constitutes the refereed proceedings of the International Conference on Spatial Information Theory, COSIT 2005, held in Elliottville, NY, USA in September 2005. The papers are organized in topical sections on vagueness, uncertainty, and gradation; paths and routes; ontologies and semantics; ontologies and spatial relations; and more.
Software Architecture ; 14th European Conference, ECSA 2020, L'Aquila, Italy, September 14–18, 2020, Proceedings
Constitutes the refereed proceedings of the 14th International Conference on Software Architecture, ECSA 2020, held in A’quila, Italy, in September 2020. In the Research Track, 12 full papers presented together with 5 short papers were carefully reviewed and selected from 103 submissions. They are organized in topical sections as follows: microservices; uncertainty, self-adaptive, and open systems; model-based approaches; performance and security engineering; architectural smells and source code analysis; education and training; experiences and learnings from industrial case studies; and architecting contemporary distributed systems.
Soft Methods for Integrated Uncertainty Modelling
This edited volume is the proceedings of the 2006 International Conference on Soft Methods in Probability and Statistics (SMPS 2006) hosted by the Artificial Intelligence Group at the University of Bristol, between 5-7 September 2006.
Soft Methods for Handling Variability and Imprecision
This book gathers contributions to the 4th International Conference on Soft methods in Probability and Statistics. Its aim is to present recent results illustrating such new trends that enlarge the statistical and uncertainty modeling traditions, towards the handling of incomplete or subjective information. It covers a broad scope ranging from philosophical and mathematical underpinnings of new uncertainty theories, with a stress on their impact in the area of statistics and data analysis, to numerical methods and applications to environmental risk analysis and mechanical engineering. A unique feature of this collection is to establish a dialogue between fuzzy random variables and imprecise probability theories.
Soft Computing in Ontologies and Semantic Web
This book covers in a great depth the fast growing topic of tools, techniques and applications of soft computing in the ontologies and Semantic Web. How components of the Semantic Web can be covered with a soft computing focus is shown. The book aims to provide a single account of current studies in soft computing approaches to the ontologies and the Semantic Web.
Soft Computing in Industrial Applications : Recent and Emerging Methods and Techniques
Soft Computing admits approximate reasoning, imprecision, uncertainty and partial truth in order to mimic aspects of the remarkable human capability of making decisions in real-life and ambiguous environments. "Soft Computing in Industrial Applications" contains a collection of papers that were presented at the 11th On-line World Conference on Soft Computing in Industrial Applications, held in September-October 2006. This carefully edited book provides a comprehensive overview of the recent advances in the industrial applications of soft computing and covers a wide range of application areas, including data analysis and data mining, computer graphics, intelligent control, systems, pattern recognition, classifiers, as well as modeling optimization. The book is aimed at researchers and practitioners who are engaged in developing and applying intelligent systems principles to solving real-world problems. It is also suitable as wider reading for science and engineering postgraduate students.
Soft Computing in Image Processing : Recent Advances
"Soft Computing in Image Processing: Recent Advances" follows the edited volumes "Fuzzy Techniques in Image Processing" (volume 52, published in 2000) and "Fuzzy Filters for Image Processing" (volume 122, published in 2003), and covers a wide range of both practical and theoretical applications of soft computing in image processing. The 16 excellent chapters of the book have been grouped into five parts: Applications in Remote Sensing, Applications in Image Retrieval, Applications in Image Analysis, Other Applications, and Theoretical Contributions. The focus of the book is on practical applications, which makes it interesting for every researcher that is involved with soft computing, image processing, or both scientific branches.
Social Security, Demographics, and Risk
In this book, we first provide an overview of thecentral issue of social security and will then take a close look at social security underuncertainty with a focus on the influence of demographics on systems of old-ageprovision.
