Enrichment of Qualitative Beliefs for Reasoning under Uncertainty

Enrichment of Qualitative Beliefs for Reasoning under Uncertainty PDF Author: Xinde Li
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 12

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Book Description
This paper deals with enriched qualitative belief functions for reasoning under uncertainty and for combining information expressed in natural language through linguistic labels.

Enrichment of Qualitative Beliefs for Reasoning under Uncertainty

Enrichment of Qualitative Beliefs for Reasoning under Uncertainty PDF Author: Xinde Li
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 12

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Book Description
This paper deals with enriched qualitative belief functions for reasoning under uncertainty and for combining information expressed in natural language through linguistic labels.

Qualitative Methods for Reasoning Under Uncertainty

Qualitative Methods for Reasoning Under Uncertainty PDF Author: Simon Parsons
Publisher: MIT Press
ISBN: 9780262161688
Category : Computers
Languages : en
Pages : 534

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Book Description
Using qualitative methods to deal with imperfect information.

Fusion of imprecise qualitative information

Fusion of imprecise qualitative information PDF Author: Xinde Li
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 12

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Book Description
In this paper, we present a new 2-tuple linguistic representation model, i.e. Distribution Function Model (DFM), for combining imprecise qualitativeinformation using fusion rules drawn from Dezert-Smarandache Theory (DSmT) framework.

Transformations of belief masses into subjective probabilities

Transformations of belief masses into subjective probabilities PDF Author: Jean Dezert
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 53

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Book Description
In this chapter, we propose in the DSmT framework, a new probabilistic transformation, called DSmP, in order to build a subjective probability measure from any basic belief assignment defined on any model of the frame of discernment. Several examples are given to show how the DSmP transformation works and we compare it to main existing transformations proposed in the literature so far. We show the advantages of DSmP over classical transformations in term of Probabilistic Information Content (PIC). The direct extension of this transformation for dealing with qualitative belief assignments is also presented. This theoretical work must increase the performances of DSmT-based hard-decision based systems as well as in soft-decision based systems in many fields where it could be used, i.e. in biometrics, medicine, robotics, surveillance and threat assessment, multisensor-multitarget tracking for military and civilian applications, etc.

Advances and Applications of DSmT for Information Fusion, Vol. 3

Advances and Applications of DSmT for Information Fusion, Vol. 3 PDF Author: Florentin Smarandache
Publisher: Infinite Study
ISBN: 1599730731
Category : Science
Languages : en
Pages : 760

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Book Description
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.

General Combination Rules for Qualitative and Quantitative Beliefs

General Combination Rules for Qualitative and Quantitative Beliefs PDF Author: ARNAUD MARTIN
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 23

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Book Description
Martin and Osswald have recently proposed many generalizations of combination rules on quantitative beliefs in order to manage the conflict and to consider the specificity of the responses of the experts. Since the experts express themselves usually in natural language with linguistic labels, Smarandache and Dezert have introduced a mathematical framework for dealing directly also with qualitative beliefs. In this paper we recall some element of our previous works and propose the new combination rules, developed for the fusion of both qualitative or quantitative beliefs.

Fusion of qualitative information using imprecise 2 -tuple labels

Fusion of qualitative information using imprecise 2 -tuple labels PDF Author: Xinde Li
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 25

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Book Description
In this chapter, Herrera-Martınez 2-tuple linguistic representation model is extended for combining imprecise qualitative information using fusion rules drawn from Dezert-Smarandache Theory (DSmT) or from Dempster-Shafer Theory (DST) frameworks.

Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5 PDF Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 931

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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.

Combination of Qualitative Information with 2-Tuple Linguistic Representation in Dezert-Smarandache Theory

Combination of Qualitative Information with 2-Tuple Linguistic Representation in Dezert-Smarandache Theory PDF Author: Xin-De Li
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 12

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Book Description
Modern systems for information retrieval, fusion and management need to deal more and more with information coming from human experts usually expressed qualitatively in natural language with linguistic labels.

Advances in Intelligent Computing - IPMU '94

Advances in Intelligent Computing - IPMU '94 PDF Author: Bernadette Bouchon-Meunier
Publisher: Springer Science & Business Media
ISBN: 9783540601166
Category : Computers
Languages : en
Pages : 648

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Book Description
This book presents a topical selection of full refereed research papers presented during the 5th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU '94, held in Paris, France in July 1994. The topical focus is on the role of uncertainty in the contruction of intelligent computing systems and it is shown how the concepts of AI, neural networks, and fuzzy logic can be utilized for that purpose. In total, there are presented 63 thoroughly revised papers organized in sections on fundamental issues; theory of evidence; networks, probabilistic, statistical, and informational methods; possibility theory, logics, chaos, reusability, and applications.