Relevant bibliographies by topics / Probabilistic Proportional Redistribution rule no.5

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Academic literature on the topic 'Probabilistic Proportional Redistribution rule no.5'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Probabilistic Proportional Redistribution rule no.5"

1

Tchamova, Albena, Jean Dezert, Nadejda Bocheva, Pavlina Konstantinova, Bilyana Genova, and Miroslava Stefanova. "A Study on Human Learning Ability during Classification of Motion and Colour Visual Cues and Their Combination." Cybernetics and Information Technologies 21, no. 1 (2021): 73–86. http://dx.doi.org/10.2478/cait-2021-0006.

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Abstract The paper presents a study on the human learning process during the classification of stimuli, defined by motion and color visual cues and their combination. Because the classification dimension and the features that define each category are uncertain, we model the learning curves using Bayesian inference and more precisely the Normalized Conjunctive Consensus rule, and also on the base of the more efficient probabilistic Proportional Conflict Redistribution rule No 5 (pPCR5) defined within Dezert-Smarandache Theory (DSmT) of plausible and paradoxical reasoning. Our goal is to study h
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2

Albena, Tchamova, Dezert Jean, Bocheva Nadejda, and Konstantinova Pavlina. "Human Integration of Motion and Texture Information in Visual Slant Estimation." September 5, 2008. https://doi.org/10.5281/zenodo.34827.

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The present research is aimed to: (i) characterize the ability of human visual system to define the objects’ slant on the base of combination of visual stimulus characteristics, that in general are uncertain and even conflicting. (ii) evaluate the influence of human age on visual cues assessment and processing; (iii) estimate the process of human visual cue integration based on the well known Normalized Conjunctive Consensus and Averaging fusion rules, as well on the base of more efficient probabilistic Proportional Conflict Redistribution rule no.5 defined within Dezert-Smarandache Theo
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3

Albena, Tchamova, Dezert Jean, Bocheva Nadejda, and Konstantinova Pavlina. "Human Integration of Motion and Texture Information in Visual Slant Estimation." July 1, 2015. https://doi.org/10.5281/zenodo.22481.

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The present research is aimed to: (i) characterize the ability of human visual system to define the objects’ slant on the base of combination of visual stimulus characteristics, that in general are uncertain and even conflicting. (ii) evaluate the influence of human age on visual cues assessment and processing; (iii) estimate the process of human visual cue integration based on the well known Normalized Conjunctive Consensus and Averaging fusion rules, as well on the base of more efficient probabilistic Proportional Conflict Redistribution rule no.
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4

Jean, Dezert, and Pannetier Benjamin. "A PCR-BIMM filter For Maneuvering Target Tracking." July 1, 2015. https://doi.org/10.5281/zenodo.22433.

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In this paper we show how to correct and improve the Belief Interacting Multiple Model filter (BIMM) proposed in 2009 by Nassreddine et al. for tracking maneuvering targets. Our improved algorithm, called PCR-BIMM is based on results developed in DSmT (Dezert-Smarandache Theory) framework and concerns two main steps of BIMM: 1) the update of the basic belief assignment of modes which is done by the Proportional Conflict Redistribution Rule no. 5 rather than Smets’ rule (conjunctive rule); 2) the global target state estimation which is obtained
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5

Albena, Tchamova, and Dezert Jean. "Intelligent Alarm Classification Based on DSmT." October 25, 2013. https://doi.org/10.5281/zenodo.34834.

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In this paper the critical issue of alarms’ classification and prioritization (in terms of degree of danger) is considered and realized on the base of Proportional Conflict Redistribution rule no.5, defined in Dezert-Smarandache Theory of plausible and paradoxical reasoning.
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6

Albena, Tchamova, and Dezert Jean. "Intelligent Alarm Classification Based on DSmT." August 14, 2012. https://doi.org/10.5281/zenodo.1042048.

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In this paper the critical issue of alarms’ classification and prioritization (in terms of degree of danger) is considered and realized on the base of Proportional Conflict Redistribution rule no.5, defined in Dezert-Smarandache Theory of plausible and paradoxical reasoning.The results obtained show the strong ability of this rule to take care in a coherent and stable way for the evolution of all possible degrees of danger, relating to a set of a priori defined, out of the ordinary dangerous directions.
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7

Florentin, Smarandache, and Dezert Jean. "Importance of Sources using the Repeated Fusion Method and the Proportional Conflict Redistribution Rules #5 and #6." September 22, 2013. https://doi.org/10.5281/zenodo.30188.

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8

Albena, Tchamova, and Dezert Jean. "Intelligent Alarm Classification Based on DSmT." July 1, 2015. https://doi.org/10.5281/zenodo.22496.

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In this paper the critical issue of alarms’ classification and prioritization (in terms of degree of danger) is considered and realized on the base of Proportional Conflict Redistribution rule no.5, defined in Dezert-Smarandache Theory ofplausibleandparadoxicalreasoning.Theresultsobtainedshow the strong ability of this rule to take care in a coherent and stable way for the evolution of all possible degrees of danger, relating to a set of a priori defined, out of the ordinary dangerous directions. A comparison with Dempster’s rule performance is also provided. Dempster’s rule show
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9

Jean, Dezert, and Tacnet Jean-Marc. "Evidential Reasoning for Multi-Criteria Analysis Based on DSmT-AHP." July 1, 2015. https://doi.org/10.5281/zenodo.22462.

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In this paper, we present an extension of the multi-criteria decision making based on the Analytic Hierarchy Process (AHP) which incorporates uncertain knowledge matrices for generating basic belief assignments (bba’s). The combination of priority vectors corresponding to bba’s related to each (sub)-criterion is performed using the Proportional Conflict Redistribution rule no. 5 proposed in Dezert-Smarandache Theory (DSmT) of plausible and paradoxical reasoning. The method presented here, called DSmT-AHP, is illustrated on very simple examples.
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10

A., Tchamova, and Dezert Jean. "Performance evaluation of fuzzy-based fusion rules for tracking applications." January 15, 2015. https://doi.org/10.5281/zenodo.22959.

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p>The objective of this paper is to present and to evaluate the performance of particularnbsp;fusion rules based on fuzzy T-Conorm/T-Norm operators for two tracking applications:nbsp;(1) Tracking object#39;s type changes, supporting the process of objects#39; identi cationnbsp;(e.g. ghter against cargo, friendly aircraft against hostile ones), which, consequentlynbsp;is essential for improving the quality of generalized data association for targets#39; track-nbsp;ing; (2) Alarms identi cation and prioritization in terms of degree of danger relatingnbsp;to a set of a priori de ned, out of th
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