Belief Functions Theory And Applications
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Belief Functions Theory And Applications
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Author : Fabio Cuzzolin
language : en
Publisher: Springer
Release Date : 2014-09-05
Belief Functions Theory And Applications written by Fabio Cuzzolin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-05 with Computers categories.
This book constitutes the thoroughly refereed proceedings of the Third International Conference on Belief Functions, BELIEF 2014, held in Oxford, UK, in September 2014. The 47 revised full papers presented in this book were carefully selected and reviewed from 56 submissions. The papers are organized in topical sections on belief combination; machine learning; applications; theory; networks; information fusion; data association; and geometry.
Belief Functions Theory And Applications
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Author : Thierry Denoeux
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-04-26
Belief Functions Theory And Applications written by Thierry Denoeux and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-26 with Technology & Engineering categories.
The theory of belief functions, also known as evidence theory or Dempster-Shafer theory, was first introduced by Arthur P. Dempster in the context of statistical inference, and was later developed by Glenn Shafer as a general framework for modeling epistemic uncertainty. These early contributions have been the starting points of many important developments, including the Transferable Belief Model and the Theory of Hints. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well understood connections to other frameworks such as probability, possibility and imprecise probability theories. This volume contains the proceedings of the 2nd International Conference on Belief Functions that was held in Compiègne, France on 9-11 May 2012. It gathers 51 contributions describing recent developments both on theoretical issues (including approximation methods, combination rules, continuous belief functions, graphical models and independence concepts) and applications in various areas including classification, image processing, statistics and intelligent vehicles.
Belief Functions Theory And Applications
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Author : Thierry Denœux
language : en
Publisher: Springer Nature
Release Date : 2021-10-12
Belief Functions Theory And Applications written by Thierry Denœux and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-12 with Computers categories.
This book constitutes the refereed proceedings of the 6th International Conference on Belief Functions, BELIEF 2021, held in Shanghai, China, in October 2021. The 30 full papers presented in this book were carefully selected and reviewed from 37 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more.
Belief Functions Theory And Applications
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Author : Sébastien Destercke
language : en
Publisher: Springer
Release Date : 2018-09-07
Belief Functions Theory And Applications written by Sébastien Destercke and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-07 with Computers categories.
This book constitutes the refereed proceedings of the 5th International Conference on Belief Functions, BELIEF 2018, held in Compiègne, France, in September 2018.The 33 revised regular papers presented in this book were carefully selected and reviewed from 73 submissions. The papers were solicited on theoretical aspects (including for example statistical inference, mathematical foundations, continuous belief functions) as well as on applications in various areas including classification, statistics, data fusion, network analysis and intelligent vehicles.
Belief Functions Theory And Applications
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Author : Jiřina Vejnarová
language : en
Publisher: Springer
Release Date : 2016-09-07
Belief Functions Theory And Applications written by Jiřina Vejnarová and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-07 with Computers categories.
This book constitutes the thoroughly refereed proceedings of the 4th International Conference on Belief Functions, BELIEF 2016, held in Prague, Czech Republic, in September 2016. The 25 revised full papers presented in this book were carefully selected and reviewed from 33 submissions. The papers describe recent developments of theoretical issues and applications in various areas such as combination rules; conflict management; generalized information theory; image processing; material sciences; navigation.
Belief Functions Theory And Applications
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Author : Sylvie Le Hégarat-Mascle
language : en
Publisher: Springer Nature
Release Date : 2022-09-29
Belief Functions Theory And Applications written by Sylvie Le Hégarat-Mascle and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-29 with Mathematics categories.
This book constitutes the refereed proceedings of the 7th International Conference on Belief Functions, BELIEF 2022, held in Paris, France, in October 2022. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well-understood connections to other frameworks such as probability, possibility, and imprecise probability theories. It has been applied in diverse areas such as machine learning, information fusion, and pattern recognition. The 29 full papers presented in this book were carefully selected and reviewed from 31 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more.
Belief Functions Theory And Applications
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Author : Yaxin Bi
language : en
Publisher: Springer Nature
Release Date : 2024-08-19
Belief Functions Theory And Applications written by Yaxin Bi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-19 with Computers categories.
This book constitutes the refereed proceedings of the 8th International Conference on Belief Functions, BELIEF 2024, held in Belfast, UK, in September 2–4, 2024. The 30 full papers presented in this book were carefully selected and reviewed from 36 submissions. The papers cover a wide range on theoretical aspects on Machine learning; Statistical inference; Information fusion and optimization; Measures of uncertainty, conflict and distances; Continuous belief functions, logics, computation.
The Geometry Of Uncertainty
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Author : Fabio Cuzzolin
language : en
Publisher: Springer Nature
Release Date : 2020-12-17
The Geometry Of Uncertainty written by Fabio Cuzzolin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-17 with Computers categories.
The principal aim of this book is to introduce to the widest possible audience an original view of belief calculus and uncertainty theory. In this geometric approach to uncertainty, uncertainty measures can be seen as points of a suitably complex geometric space, and manipulated in that space, for example, combined or conditioned. In the chapters in Part I, Theories of Uncertainty, the author offers an extensive recapitulation of the state of the art in the mathematics of uncertainty. This part of the book contains the most comprehensive summary to date of the whole of belief theory, with Chap. 4 outlining for the first time, and in a logical order, all the steps of the reasoning chain associated with modelling uncertainty using belief functions, in an attempt to provide a self-contained manual for the working scientist. In addition, the book proposes in Chap. 5 what is possibly the most detailed compendium available of all theories of uncertainty. Part II, The Geometry of Uncertainty, is the core of this book, as it introduces the author’s own geometric approach to uncertainty theory, starting with the geometry of belief functions: Chap. 7 studies the geometry of the space of belief functions, or belief space, both in terms of a simplex and in terms of its recursive bundle structure; Chap. 8 extends the analysis to Dempster’s rule of combination, introducing the notion of a conditional subspace and outlining a simple geometric construction for Dempster’s sum; Chap. 9 delves into the combinatorial properties of plausibility and commonality functions, as equivalent representations of the evidence carried by a belief function; then Chap. 10 starts extending the applicability of the geometric approach to other uncertainty measures, focusing in particular on possibility measures (consonant belief functions) and the related notion of a consistent belief function. The chapters in Part III, Geometric Interplays, are concerned with the interplay of uncertainty measures of different kinds, and the geometry of their relationship, with a particular focus on the approximation problem. Part IV, Geometric Reasoning, examines the application of the geometric approach to the various elements of the reasoning chain illustrated in Chap. 4, in particular conditioning and decision making. Part V concludes the book by outlining a future, complete statistical theory of random sets, future extensions of the geometric approach, and identifying high-impact applications to climate change, machine learning and artificial intelligence. The book is suitable for researchers in artificial intelligence, statistics, and applied science engaged with theories of uncertainty. The book is supported with the most comprehensive bibliography on belief and uncertainty theory.
Belief Functions
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Author : Sylvie Le Hégarat-Mascle
language : en
Publisher:
Release Date : 2022
Belief Functions written by Sylvie Le Hégarat-Mascle and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Decision making categories.
This book constitutes the refereed proceedings of the 7th International Conference on Belief Functions, BELIEF 2022, held in Paris, France, in October 2022. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well-understood connections to other frameworks such as probability, possibility, and imprecise probability theories. It has been applied in diverse areas such as machine learning, information fusion, and pattern recognition. The 29 full papers presented in this book were carefully selected and reviewed from 31 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more.
Optimum Decision Making In Asset Management
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Author : Carnero, María Carmen
language : en
Publisher: IGI Global
Release Date : 2016-08-24
Optimum Decision Making In Asset Management written by Carnero, María Carmen and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-24 with Business & Economics categories.
Asset management is becoming increasingly important to an organization’s strategy, given its effects on cost, production, and quality. No matter the sector, important decisions are made based on techniques and theories that are thought to optimize results; asset management models and techniques could help maximize effectiveness while reducing risk. Optimum Decision Making in Asset Management posits that effective decision making can be augmented by asset management based on mathematical techniques and models. Resolving the problems associated with minimizing uncertainty, this publication outlines a myriad of methodologies, procedures, case studies, and management tools that can help any organization achieve world-class maintenance. This book is ideal for managers, manufacturing engineers, programmers, academics, and advanced management students.