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Author: Hongyan Sun
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 31
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Book Description
In this chapter, the Dempster-Shafer (DS) combination rule is examined based on the multi-valued mapping (MVM) and the product combination rule of multiple independent sources of information.
Author: Hongyan Sun
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 31
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Book Description
In this chapter, the Dempster-Shafer (DS) combination rule is examined based on the multi-valued mapping (MVM) and the product combination rule of multiple independent sources of information.
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN: 1931233829
Category : Computers
Languages : en
Pages : 438
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Book Description
Papers collected from researchers in fusion information, such as: Florentin Smarandache, Jean Dezert, Hongshe Dang, Chongzhao Han, Frederic Dambreville, Milan Daniel, Mohammad Khoshnevisan, Sukanto Bhattacharya, Albena Tchamova, Tzvetan Semerdjiev, Pavlina Konstantinova, Hongyan Sun, Mohammad Farooq, John J. Sudano, Samuel Corgne, Gregoire Mercier, Laurence Hubert-Moy, Anne-Laure Jousselme, Patrick Maupin and others on Dezert-Smarandache Theory of Plausible and Paradoxical Reasoning (DSmT).. The principal theories available until now for data fusion are the probability theory, the fuzzy set theory, the possibility theory, the hint theory and the theory of evidence. Since last two years J. Dezert and F. Smarandache are actively developing a new theory of plausible and paradoxical reasoning, called DSmT (acronym for Dezert-Smarandache Theory), for information fusion of uncertain and highly conflicting sources of information. The DSmT can be interpreted as a generalization of the Dempster-Shafer Theory (DST) but goes far beyond the DST. The free-DSmT model, which assumes that the ultimate refinement of the frame of discernment of the fusion problem is not accessible due to the intrinsic nature of its elements, is opposite to the Shafer's model (on which is based the DST) assuming the exhaustivity and exclusivity of all elements of the frame of discernment. The DSmT proposes a new theoretical framework for data fusion based on definition of hyper-power sets and a new simple commutative and associative rule of combination. Recently, it has been discovered, through a new DSm hybrid rule of combination, that DSmT can be also extended to problems involving hybrid-models (models including some exclusivity and/or non-existentially constraints). This new important theoretical result offers now to the DSmT a wider class of fusion applications and allows potentially to attack the next generation of complex dynamical/temporal fusion problems. DSmT can also provide a theoretical issue for the fusion of neutrosophic information (extension of fuzzy information proposed by F. Smarandache in nineties - see http://www.gallup.unm.edu/~smarandache/FirstNeutConf.htm for details about the neutrosophy logic and neutrosophy set theory).
Author:
Publisher: IOS Press
ISBN:
Category :
Languages : en
Pages : 6097
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Book Description
Author: Weiru Liu
Publisher: Springer
ISBN: 3642221521
Category : Computers
Languages : en
Pages : 775
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Book Description
This book constitutes the refereed proceedings of the 11th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2011, held in Belfast, UK, in June/July 2011. The 60 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 108 submissions. The papers are organized in topical sections on argumentation; Bayesian networks and causal networks; belief functions; belief revision and inconsistency handling; classification and clustering; default reasoning and logics for reasoning under uncertainty; foundations of reasoning and decision making under uncertainty; fuzzy sets and fuzzy logic; implementation and applications of uncertain systems; possibility theory and possibilistic logic; and uncertainty in databases.
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 33
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Book Description
This chapter may look like a glossary of the fusion rules and we also introduce new ones presenting their formulas and examples.
Author: Eyke Hüllermeier
Publisher: Springer
ISBN: 3642140491
Category : Computers
Languages : en
Pages : 786
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Book Description
The book constitutes the refereed proceedings of the 13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2010, held in Dortmund, Germany from June 28 - July 2, 2010. The 77 revised full papers were carefully reviewed and selected from 320 submissions and reflect the richness of research in the field of Computational Intelligence and represent developments on topics as: machine learning, data mining, pattern recognition, uncertainty handling, aggregation and fusion of information as well as logic and knowledge processing.
Author: Fabio Cuzzolin
Publisher: Springer Nature
ISBN: 3030631532
Category : Computers
Languages : en
Pages : 850
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Book Description
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.
Author: Kari Sentz
Publisher:
ISBN:
Category : Dempster-Shafer theory
Languages : en
Pages : 100
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Book Description
Dempster-Shafer theory offers an alternative to traditional probabilistic theory for the mathematical representation of uncertainty. The significant innovation of this framework is that it allows for the allocation of a probability mass to sets or intervals. Dempster-Shafer theory does not require an assumption regarding the probability of the individual constituents of the set or interval. This is a potentially valuable tool for the evaluation of risk and reliability in engineering applications when it is not possible to obtain a precise measurement from experiments, or when knowledge is obtained from expert elicitation. An important aspect of this theory is the combination of evidence obtained from multiple sources and the modeling of conflict between them. This report surveys a number of possible combination rules for Dempster-Shafer structures and provides examples of the implementation of these rules for discrete and interval-valued data.
Author: Eric Lefebvre
Publisher: IOS Press
ISBN: 1586037277
Category : Business & Economics
Languages : en
Pages : 412
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Book Description
"Proceedings of the NATO Advanced Study Institute on Multisensor Data and Information Processing for Rapid and Robust Situation and Threat Assessment, Albena, Bulgaria, 16-27 May 2005"--T.p. verso.
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category : Biography & Autobiography
Languages : en
Pages : 932
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Book Description
This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 (available at fs.unm.edu/DSmT-book4.pdf or www.onera.fr/sites/default/files/297/2015-DSmT-Book4.pdf) in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well. We want to thank all the contributors of this fifth volume for their research works and their interests in the development of DSmT, and the belief functions. We are grateful as well to other colleagues for encouraging us to edit this fifth volume, and for sharing with us several ideas and for their questions and comments on DSmT through the years. We thank the International Society of Information Fusion (www.isif.org) for diffusing main research works related to information fusion (including DSmT) in the international fusion conferences series over the years. Florentin Smarandache is grateful to The University of New Mexico, U.S.A., that many times partially sponsored him to attend international conferences, workshops and seminars on Information Fusion. Jean Dezert is grateful to the Department of Information Processing and Systems (DTIS) of the French Aerospace Lab (Office National d’E´tudes et de Recherches Ae´rospatiales), Palaiseau, France, for encouraging him to carry on this research and for its financial support. Albena Tchamova is first of all grateful to Dr. Jean Dezert for the opportunity to be involved during more than 20 years to follow and share his smart and beautiful visions and ideas in the development of the powerful Dezert-Smarandache Theory for data fusion. She is also grateful to the Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, for sponsoring her to attend international conferences on Information Fusion.
