THE PRINCIPLES OF UNCERTAINTY

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The Principles Of Uncertainty

Author : Maira Kalman
ISBN : 159420134X
Genre : Art
File Size : 51.24 MB
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A narrative travelogue told in handwritten text and illustrations presents the creator's idiosyncratic worldview on a broad range of topics, from personal identity and happiness to the reasons for war and the delights of candy. 100,000 first printing.
Category: Art

Principles Of Uncertainty And Other Constants

Author : Mitch Levenberg
ISBN : 9780595378340
Genre : Fiction
File Size : 79.1 MB
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Levenberg.has a sharp merciless eye for the hazards that can intervene in the seemingly most innocuous situation. He is utterly fearless in describing the human situation as it is. At the same time humor shines through everything he writes. Alfred Kazin/Literary Critic Mitch Levenberg is a masterful storyteller. His characters walk a very fine line between the humorous and the pathetic, the farcical and the heroic as their everyday lives turn into an eerie high wire act. The results are unforgettable. Paul Violi/Poet and Critic Mitch Levenberg beautifully and poetically captures the sense of dislocation, both literal and figurative a person can feel. He writes of things seen but not quite believed, of moments where the narrator doubts his own perceptions.of the way things are. His grasp of sometimes unseen connections between people and events make his stories more than just travelogues or observations; they help cut deeper, in some cases painfully so, linking events to emotions the characters do not wish to recognize or reckon with. Glenn Raucher/Writer's Voice
Category: Fiction

The Principles Of Uncertainty

Author : Ernan McMullin
ISBN : OCLC:42190657
Genre : Heisenberg uncertainty principle
File Size : 87.44 MB
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Category: Heisenberg uncertainty principle

Principles Of Uncertainty

Author : Joseph B. Kadane
ISBN : 9781439861622
Genre : Mathematics
File Size : 86.24 MB
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An intuitive and mathematical introduction to subjective probability and Bayesian statistics. An accessible, comprehensive guide to the theory of Bayesian statistics, Principles of Uncertainty presents the subjective Bayesian approach, which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods. Both rigorous and friendly, the book contains: Introductory chapters examining each new concept or assumption Just-in-time mathematics – the presentation of ideas just before they are applied Summary and exercises at the end of each chapter Discussion of maximization of expected utility The basics of Markov Chain Monte Carlo computing techniques Problems involving more than one decision-maker Written in an appealing, inviting style, and packed with interesting examples, Principles of Uncertainty introduces the most compelling parts of mathematics, computing, and philosophy as they bear on statistics. Although many books present the computation of a variety of statistics and algorithms while barely skimming the philosophical ramifications of subjective probability, this book takes a different tack. By addressing how to think about uncertainty, this book gives readers the intuition and understanding required to choose a particular method for a particular purpose.
Category: Mathematics

Uncertainty And Information

Author : George J. Klir
ISBN : 9780471755562
Genre : Technology & Engineering
File Size : 43.7 MB
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Deal with information and uncertainty properly and efficiently using tools emerging from generalized information theory Uncertainty and Information: Foundations of Generalized Information Theory contains comprehensive and up-to-date coverage of results that have emerged from a research program begun by the author in the early 1990s under the name "generalized information theory" (GIT). This ongoing research program aims to develop a formal mathematical treatment of the interrelated concepts of uncertainty and information in all their varieties. In GIT, as in classical information theory, uncertainty (predictive, retrodictive, diagnostic, prescriptive, and the like) is viewed as a manifestation of information deficiency, while information is viewed as anything capable of reducing the uncertainty. A broad conceptual framework for GIT is obtained by expanding the formalized language of classical set theory to include more expressive formalized languages based on fuzzy sets of various types, and by expanding classical theory of additive measures to include more expressive non-additive measures of various types. This landmark book examines each of several theories for dealing with particular types of uncertainty at the following four levels: * Mathematical formalization of the conceived type of uncertainty * Calculus for manipulating this particular type of uncertainty * Justifiable ways of measuring the amount of uncertainty in any situation formalizable in the theory * Methodological aspects of the theory With extensive use of examples and illustrations to clarify complex material and demonstrate practical applications, generous historical and bibliographical notes, end-of-chapter exercises to test readers' newfound knowledge, glossaries, and an Instructor's Manual, this is an excellent graduate-level textbook, as well as an outstanding reference for researchers and practitioners who deal with the various problems involving uncertainty and information. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Category: Technology & Engineering

Principles Of Modeling Uncertainties In Spatial Data And Spatial Analyses

Author : Wenzhong Shi
ISBN : 1420059289
Genre : Technology & Engineering
File Size : 36.1 MB
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When compared to classical sciences such as math, with roots in prehistory, and physics, with roots in antiquity, geographical information science (GISci) is the new kid on the block. Its theoretical foundations are therefore still developing and data quality and uncertainty modeling for spatial data and spatial analysis is an important branch of that theory. Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses outlines the foundational principles and supplies a firm grasp of the disciplines’ theoretical underpinnings. Comprehensive, Systematic Review of Methods for Handling Uncertainties The book summarizes the principles of modeling uncertainty of spatial data and spatial analysis, and then introduces the developed methods for handling uncertainties in spatial data and modeling uncertainties in spatial models. Building on this foundation, the book goes on to explore modeling uncertainties in spatial analyses and describe methods for presentation of data as quality information. Progressing from basic to advanced topics, the organization of the contents reflects the four major theoretical breakthroughs in uncertainty modeling: advances in spatial object representation, uncertainty modeling for static spatial data to dynamic spatial analyses, uncertainty modeling for spatial data to spatial models, and error description of spatial data to spatial data quality control. Determine Fitness-of-Use for Your Applications Modeling uncertainties is essential for the development of geographic information science. Uncertainties always exist in GIS and are then propagated in the results of any spatial analysis. The book delineates how GIS can be a better tool for decision-making and demonstrates how the methods covered can be used to control the data quality of GIS products.
Category: Technology & Engineering

Information Theory And Artificial Intelligence To Manage Uncertainty In Hydrodynamic And Hydrological Models

Author : Abebe Andualem Jemberie
ISBN : 9058096955
Genre : Science
File Size : 67.62 MB
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The complementary nature of physically-based and data-driven models in their demand for physical insight and historical data, leads to the notion that the predictions of a physically-based model can be improved and the associated uncertainty can be systematically reduced through the conjunctive use of a data-driven model of the residuals. The objective of this thesis is to minimise the inevitable mismatch between physically-based models and the actual processes as described by the mismatch between predictions and observations. Principles based on information theory are used to detect the presence and nature of residual information in model errors that might help to develop a data-driven model of the residuals by treating the gap between the process and its (physically-based) model as a separate process. The complementary modelling approach is applied to various hydrodynamic and hydrological models to forecast the expected errors and accuracy, using neural network and fuzzy rule-based models. Complementary modelling offers the opportunity of incorporating processes and data that are not considered by the model, without affecting the routine operation of physically-based models. The possibility that information may be obtained which will help to improve the physically-based model is also demonstrated.
Category: Science

Uncertainty Based Information

Author : George Klir
ISBN : 9783790818697
Genre : Mathematics
File Size : 26.6 MB
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Information is precious. It reduces our uncertainty in making decisions. Knowledge about the outcome of an uncertain event gives the possessor an advantage. It changes the course of lives, nations, and history itself. Information is the food of Maxwell's demon. His power comes from know ing which particles are hot and which particles are cold. His existence was paradoxical to classical physics and only the realization that information too was a source of power led to his taming. Information has recently become a commodity, traded and sold like or ange juice or hog bellies. Colleges give degrees in information science and information management. Technology of the computer age has provided access to information in overwhelming quantity. Information has become something worth studying in its own right. The purpose of this volume is to introduce key developments and results in the area of generalized information theory, a theory that deals with uncertainty-based information within mathematical frameworks that are broader than classical set theory and probability theory. The volume is organized as follows.
Category: Mathematics