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The Generalized Pignistic Transformation


The Generalized Pignistic Transformation
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A Generalized Pignistic Transformation


A Generalized Pignistic Transformation
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Author : Jean Dezert
language : en
Publisher: Infinite Study
Release Date :

A Generalized Pignistic Transformation written by Jean Dezert and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.


This chapter introduces a generalized pignistic transformation (GPT) developed in the DSmT framework as a tool for decision-making at the pignistic level. The GPT allows to construct quite easily a subjective probability measure from any generalized basic belief assignment provided by any corpus of evidence. We focus our presentation on the 3D case and we provide the full result obtained by the proposed GPT and its validation drawn from the probability theory.



Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 5


Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 5
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Author : Florentin Smarandache
language : en
Publisher: Infinite Study
Release Date : 2023-12-27

Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 5 written by Florentin Smarandache and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-27 with Biography & Autobiography categories.


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.



Design Of A Framework To Facilitate Decisions Using Information Fusion


Design Of A Framework To Facilitate Decisions Using Information Fusion
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Author : Tamer M. Abo Neama
language : en
Publisher: Infinite Study
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Design Of A Framework To Facilitate Decisions Using Information Fusion written by Tamer M. Abo Neama and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.


Information fusion is an advanced research area which can assist decision makers in enhancing their decisions. This paper aims at designing a new multi-layer framework that can support the process of performing decisions from the obtained beliefs using information fusion. Since it is not an easy task to cross the gap between computed beliefs of certain hypothesis and decisions, the proposed framework consists of the following layers in order to provide a suitable architecture.



An Introduction To Dsmt In Information Fusion


An Introduction To Dsmt In Information Fusion
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Author : Jean Dezert
language : en
Publisher: Infinite Study
Release Date :

An Introduction To Dsmt In Information Fusion written by Jean Dezert and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.


The management and combination of uncertain, imprecise, fuzzy and even paradoxical or highly confliicting sources of information has always been, and still remains today, of primal importance for the development of reliable modern information systems involving artificial reasoning. In this introduction, we present a survey of our recent theory of plausible and paradoxical reasoning, known as Dezert-Smarandache Theory (DSmT), developed for dealing with imprecise, uncertain and conflicting sources of information. We focus our presentation on the foundations of DSmT and on its most important rules of combination, rather than on browsing specific applications ofDSmT available in literature. Several simple examples are given throughout this presentation to show the effciency and the generality of this new theory.



Implementing General Belief Function Framework With A Practical Codi Cation For Low Complexity


Implementing General Belief Function Framework With A Practical Codi Cation For Low Complexity
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Author : Arnaud Martin
language : en
Publisher: Infinite Study
Release Date :

Implementing General Belief Function Framework With A Practical Codi Cation For Low Complexity written by Arnaud Martin and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.


In this chapter, we propose a new practical codification of the elements of the Venn diagram in order to easily manipulate the focal elements. In order to reduce the complexity, the eventual constraints must be integrated in the codification at the beginning.



Advances And Applications Of Dsmt For Information Fusion Vol 3


Advances And Applications Of Dsmt For Information Fusion Vol 3
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Author : Florentin Smarandache
language : en
Publisher: Infinite Study
Release Date : 2004

Advances And Applications Of Dsmt For Information Fusion Vol 3 written by Florentin Smarandache and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Science categories.


This volume has about 760 pages, split into 25 chapters, from 41 contributors. First part of this book presents advances of Dezert-Smarandache Theory (DSmT) which is becoming one of the most comprehensive and flexible fusion theory based on belief functions. It can work in all fusion spaces: power set, hyper-power set, and super-power set, and has various fusion and conditioning rules that can be applied depending on each application. Some new generalized rules are introduced in this volume with codes for implementing some of them. For the qualitative fusion, the DSm Field and Linear Algebra of Refined Labels (FLARL) is proposed which can convert any numerical fusion rule to a qualitative fusion rule. When one needs to work on a refined frame of discernment, the refinement is done using Smarandache¿s algebraic codification. New interpretations and implementations of the fusion rules based on sampling techniques and referee functions are proposed, including the probabilistic proportional conflict redistribution rule. A new probabilistic transformation of mass of belief is also presented which outperforms the classical pignistic transformation in term of probabilistic information content. The second part of the book presents applications of DSmT in target tracking, in satellite image fusion, in snow-avalanche risk assessment, in multi-biometric match score fusion, in assessment of an attribute information retrieved based on the sensor data or human originated information, in sensor management, in automatic goal allocation for a planetary rover, in computer-aided medical diagnosis, in multiple camera fusion for tracking objects on ground plane, in object identification, in fusion of Electronic Support Measures allegiance report, in map regenerating forest stands, etc.



An Introduction To Dsmt


An Introduction To Dsmt
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Author : Jean Dezert
language : en
Publisher: Infinite Study
Release Date :

An Introduction To Dsmt written by Jean Dezert and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.


The management and combination of uncertain, imprecise, fuzzy and even paradoxical or highly conflicting sources of information has always been, and still remains today, of primal importance for the development of reliable modern information systems involving artificial reasoning.



Generalized Proportional Con Ict Redistribution Rule Applied To Sonar Imagery And Radar Targets Classi Cation


Generalized Proportional Con Ict Redistribution Rule Applied To Sonar Imagery And Radar Targets Classi Cation
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Author : Arnaud Martin
language : en
Publisher: Infinite Study
Release Date :

Generalized Proportional Con Ict Redistribution Rule Applied To Sonar Imagery And Radar Targets Classi Cation written by Arnaud Martin and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.


In this chapter, we present two applications in information fusion in order to evaluate the generalized proportional conflict redistribution rule presented in chapter [7]. Most of the time the combination rules are evaluated only on simple examples. We study here different combination rules and compare them in terms of decision on real data. Indeed, in real applications, we need a reliable decision and it is the final results that matter. Two applications are presented here: a fusion of human experts opinions on the kind of underwater sediments depicted on a sonar image and a classifier fusion for radar targets recognition.



Partial Ordering On Hyper Power Sets


Partial Ordering On Hyper Power Sets
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Author : Jean Dezert
language : en
Publisher: Infinite Study
Release Date :

Partial Ordering On Hyper Power Sets written by Jean Dezert and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.


In this chapter, we examine several issues for ordering or partially or dering elements of hyper-power sets involved in the DSmT. We will show the benefit of some of these issues to obtain a nice and interesting structure of matrix represen tation of belief functions.



Advances In Computational Intelligence Part Iii


Advances In Computational Intelligence Part Iii
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Author : Salvatore Greco
language : en
Publisher: Springer
Release Date : 2012-07-20

Advances In Computational Intelligence Part Iii written by Salvatore Greco and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-20 with Computers categories.


These four volumes (CCIS 297, 298, 299, 300) constitute the proceedings of the 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012, held in Catania, Italy, in July 2012. The 258 revised full papers presented together with six invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on fuzzy machine learning and on-line modeling; computing with words and decision making; soft computing in computer vision; rough sets and complex data analysis: theory and applications; intelligent databases and information system; information fusion systems; philosophical and methodological aspects of soft computing; basic issues in rough sets; 40th anniversary of the measures of fuziness; SPS11 uncertainty in profiling systems and applications; handling uncertainty with copulas; formal methods to deal with uncertainty of many-valued events; linguistic summarization and description of data; fuzzy implications: theory and applications; sensing and data mining for teaching and learning; theory and applications of intuitionistic fuzzy sets; approximate aspects of data mining and database analytics; fuzzy numbers and their applications; information processing and management of uncertainty in knowledge-based systems; aggregation functions; imprecise probabilities; probabilistic graphical models with imprecision: theory and applications; belief function theory: basics and/or applications; fuzzy uncertainty in economics and business; new trends in De Finetti's approach; fuzzy measures and integrals; multicriteria decision making; uncertainty in privacy and security; uncertainty in the spirit of Pietro Benvenuti; coopetition; game theory; probabilistic approach.