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Journal articles on the topic 'Proportional conflict redistribution (PCR)'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

ABBAS, NASSIM, and YOUCEF CHIBANI. "SVM-DSmT COMBINATION FOR THE SIMULTANEOUS VERIFICATION OF OFF-LINE AND ON-LINE HANDWRITTEN SIGNATURES." International Journal of Computational Intelligence and Applications 11, no. 03 (2012): 1250018. http://dx.doi.org/10.1142/s1469026812500186.

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A combination handwritten signature verification system is proposed for managing conflicts provided from each individual off-line and on-line support vector machine (SVM), respectively. Basically, the system is divided into three parts: (i) Off-line verification system, (ii) on-line verification system and (iii) combination module using belief function theory. The proposed framework allows combining the normalized SVM outputs and uses an estimation technique based on the dissonant model of Appriou to compute the belief assignments. Combination is performed using belief models such as Dempster-

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2

Walia, Gurjit Singh, and Rajiv Kapoor. "Online Object Tracking via Novel Adaptive Multicue Based Particle Filter Framework for Video Surveillance." International Journal on Artificial Intelligence Tools 27, no. 06 (2018): 1850023. http://dx.doi.org/10.1142/s0218213018500239.

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Multicue based object tracking frameworks have been extensively explored due to their numerous applications in the field of computer vision. However, the online adaptive fusion of multicue under scale and illumination variations, partial or full occlusion, background clutters and object deformation remains an open challenge problem. In order to address this, we propose an online visual tracking algorithm using adaptive integration of multicue in a particle filter framework. The particle level fusion process is modelled as Shafer’s model with a power set defined over two focal elements. Partial

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3

Bartashevich, Palina, and Sanaz Mostaghim. "Multi-featured collective perception with Evidence Theory: tackling spatial correlations." Swarm Intelligence 15, no. 1-2 (2021): 83–110. http://dx.doi.org/10.1007/s11721-021-00192-8.

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AbstractCollective perception allows sparsely distributed agents to form a global view on a common spatially distributed problem without any direct access to global knowledge and only based on a combination of locally perceived information. However, the evidence gathered from the environment is often subject to spatial correlations and depends on the movements of the agents. The latter is not always easy to control and the main question is how to share and to combine the estimated information to achieve the most precise global estimate in the least possible time. The current article aims at an

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Pietkiewicz, Tadeusz. "Fusion of Identification Information from ESM Sensors and Radars Using Dezert–Smarandache Theory Rules." Remote Sensing 15, no. 16 (2023): 3977. http://dx.doi.org/10.3390/rs15163977.

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This paper presents a method of fusion of identification (attribute) information provided by two types of sensors: combined primary and secondary (IFF) surveillance radars and ESMs (electronic support measures). In the first section, the basic taxonomy of attribute identification is adopted in accordance with the standards of STANAG 1241 ed. 5 and STANAG 1241 ed. 6 (draft). These standards provide the following basic values of the attribute identifications: FRIEND; HOSTILE; NEUTRAL; UNKNOWN; and additional values, namely ASSUMED FRIEND and SUSPECT. The basis of theoretical considerations is De

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Alpert, Sofiia. "A new approach to the application of conflict redistribution rule in Satellite Image Classification." Ukrainian journal of remote sensing, no. 25 (June 25, 2020): 12–16. http://dx.doi.org/10.36023/ujrs.2020.25.171.

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Nowadays solution of different scientific problems using satellite images, generally includes a classification procedure. Classification is one of the most important procedures used in remote sensing, because it involves a lot of mathematical operations and data preprocessing. The processing of information and combining of conflicting data is a very difficult problem in classification tasks. Nowadays many classification methods are applied in remote sensing. Classification of conflicting data has been a key problem, both from a theoretical and practical point of view. But a lot of known classi

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6

SMARANDACHE, FLORENTIN, and JEAN DEZERT. "UNIFORM AND PARTIALLY UNIFORM REDISTRIBUTION RULES." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 19, no. 06 (2011): 921–37. http://dx.doi.org/10.1142/s0218488511007404.

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This paper introduces two new fusion rules for combining quantitative basic belief assignments. These rules although very simple have not been proposed in literature so far and could serve as useful alternatives because of their low computation cost with respect to the recent advanced Proportional Conflict Redistribution rules developed in the DSmT framework.

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Fu, Yaowen, and Wei Yang. "Combination Rule Based on Proportional Redistribution of Generalized Conflict for Evidence Theory." Chinese Journal of Electronics 23, no. 3 (2014): 533–38. https://doi.org/10.23919/cje.2014.10851200.

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8

Sumathi, B. "Enhance the Performance of Back Propagation Algorithm Using Proportional Conflict Redistribution Rule for the Diagnosis of Hypertension." International Journal of Computer Sciences and Engineering 6, no. 9 (2018): 215–19. http://dx.doi.org/10.26438/ijcse/v6i9.215219.

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9

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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Liang, Wei Tai, Jian Gao, and Jin Pei Yang. "A Threat Sorting Approach Based on the Fuzzy Beliefs." Applied Mechanics and Materials 235 (November 2012): 111–16. http://dx.doi.org/10.4028/www.scientific.net/amm.235.111.

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To overcome the limitations of the traditional threat assessment algorithms, a new threat sorting approach based on the fuzzy belief is proposed in this paper. In the new approach, the threat degrees described by quantitative number, interval number or linguistic label are all converted into the triangular fuzzy beliefs. The proportional conflict redistribution rule is used to combine the threat degrees of the same kind of assessment factors, the decision discounting rule is used to combine the threat degrees of different kinds of assessment factors, and the centroid method is utilized to make

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11

Fang, Yingwu. "Moving targets visual tracking in complex scenes based on PCR6 combine rules." Optica Applicata 54, no. 4 (2025): 609–24. https://doi.org/10.37190/oa/195796.

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The aim of this article is to investigate multi-moving targets visual tracking in complex scenes based on PCR6 (proportional conflict redistribution 6) combine rules, and improve the poor tracking performance in complex scenes. A tracking model of multi-moving targets was established by combining the color, edge and texture features of the targets, and the corresponding tracking algorithm was designed based on the framework of PF (particle filters) and PCR6 rules. The tracking process of moving targets including different scenes of mutual occlusion, proportion or illumination change was analyz

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12

HUANG, XINHAN, XINDE LI, MIN WANG, and JEAN DEZERT. "A FUSION MACHINE BASED ON DSMT AND PCR5 FOR ROBOT'S MAP RECONSTRUCTION." International Journal of Information Acquisition 03, no. 03 (2006): 201–11. http://dx.doi.org/10.1142/s0219878906000964.

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Characteristics of uncertainty, imprecision, and even imperfection are presented from knowledge acquisition in map reconstruction using sonar sensors fixed on autonomous mobile robot. In order to improve the precision of the fusion and performances of map reconstruction, we propose in this paper a new fusion machine based on Dezert-Smarandache Theory (DSmT) coupled with the fifth Proportional Conflict Redistribution rule (PCR5) for dealing with uncertain and conflicting evidences provided by homogeneous or heterogeneous sources of information. We propose a belief model for sonar grid map and s

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Shved, A. V. "DEVELOPMENT OF TECHNIQUE FOR DETERMINING THE MEMBERSHIP FUNCTION VALUES ON THE BASIS OF GROUP EXPERT ASSESSMENT IN FUZZY DECISION TREE METHOD." Radio Electronics, Computer Science, Control, no. 2 (June 27, 2024): 106. http://dx.doi.org/10.15588/1607-3274-2024-2-11.

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Context. Recently, fuzzy decision trees have become widely used in solving the classification problem. In the absence of objective information to construct the membership function that shows the degrees of belongingness of elements to tree nodes, the only way to obtain information is to involve experts. In the case of group decision making, the task of aggregation of experts’ preferences in order to synthesize a group decision arises. The object of the study is group expert preferences of the degree of belonging (membership function) of an element to a given class, attribute, which require str

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Selvakumar, Kandaswamy, Senthamilselvan Bavithra, Gunasekaran Krishnamoorthy, and Jagadeesan Arunakaran. "Impact of quercetin on tight junctional proteins and BDNF signaling molecules in hippocampus of PCBs-exposed rats." Interdisciplinary Toxicology 11, no. 4 (2018): 294–305. http://dx.doi.org/10.2478/intox-2018-0029.

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Abstract Polychlorinated biphenyls (PCBs) consist of a range of toxic substances which are directly proportional to carcinogenesis and tumor-promoting factors as well as having neurotoxic properties. Reactive oxygen species, which are produced from PCBs, alter blood–brain barrier (BBB) integrity, which is paralleled by cytoskeletal rearrangements and redistribution and disappearance of tight junction proteins (TJPs) like claudin-5 and occludin. Brain-derived neurotrophic factor (BDNF), plays an important role in the maintenance, survival of neurons and synaptic plasticity. It is predominant in

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15

Li, Hongfei, Hongbin Jin, Kangsheng Tian, and Xiaoyan Fei. "Analysis and Improvement for Proportional Conflict Redistribution Rules." February 5, 2010. https://doi.org/10.5281/zenodo.34753.

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The Proportional Conflict Redistribution (PCR) rules based on Dezert-Smarandache theory (DSmT) is a useful method for dealing with uncertainty problems. It is more efficient in combining conflicting evidence.

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16

Florentin, Smarandache, and Dezert Jean. "Extended PCR Rules for Dynamic Frames." October 2, 2014. https://doi.org/10.5281/zenodo.30164.

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In most of classical fusion problems modeled from belief functions, the frame of discernment is considered as static. This means that the set of elements in the frame and the underlying integrity constraints of the frame are fixed forever and they do not change with time. In some applications, like in target tracking for example, the use of such invariant frame is not very appropriate because it can truly change with time. So it is necessary to adapt the Proportional Conflict Redistribution fusion rules (PCR5 and PCR6) for working with dynamical frames.

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17

Roman, Ilin, and Blasch Erik. "Information Fusion with Belief Functions: a comparison of Proportional Conflict Redistribution PCR5 and PCR6 rules for Networked Sensors." July 6, 2015. https://doi.org/10.5281/zenodo.23211.

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We compare several belief fusion methods, including the proportional conflict redistribution rules (PCR5 and PCR6) for multiple sources. The PCR fusion of evidence methods have shown improvement over the classical Dempster-Shafer and Bayesian fusion techniques in the presence of conflicting information. The PCR6 rule shows improvement over PCR5 when the number of sources increases. Using Hasse graphical diagrams, we highlight the comparison between the methods. To our knowledge, this is the first such comparison between PCR5 and PCR6 with more than two source

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18

Erik, Blasch, Al-Nashif Youssif, and Hariri Salim. "Static versus Dynamic Data Information Fusion Analysis using DDDAS for Cyber Security Trust." July 1, 2015. https://doi.org/10.5281/zenodo.22653.

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Information fusion includes signals, features, and decision-level analysis over various types of data including imagery, text, and cyber security detection. With the maturity of data processing, the explosion of big data, and the need for user acceptance; the Dynamic Data-Driven Application System (DDDAS) philosophy fosters insights into the usability of information systems solutions. In this paper, we explore a notion of an adaptive adjustment of secure communication trust analysis that seeks a balance between standard static solutions versus dynamic-data driven

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19

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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20

Erik, P. Blasch, Dezert Jean, and Valin Pierre. "DSmT Applied to Seismic and Acoustic Sensor Fusion." July 1, 2015. https://doi.org/10.5281/zenodo.22449.

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In this paper, we explore the use of DSMT for seismic and acoustic sensor fusion. The seismic/acoustic data is noisy which leads to classification errors and conflicts in declarations. DSmT affords the redistribution of masses when there is a conflict. The goal of this paper is to present an application and comparison on DSMT with other classifier methods to include the support vector machine(SVM) and Dempster-Shafer methods. The work is based on two key references (1) Marco Duarte with the initial SVM classifier application of the seismic and acoustic s

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21

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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22

Jean, Dezert, Tchamova MIbena, Semerdjiev Tzvetan, and Konstantinova Pavlina. "Performance Evaluation of Fusion Rules For Multitarget Tracking in Clutter Based on Generalized Data Association." July 6, 2005. https://doi.org/10.5281/zenodo.34875.

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In this paper, we present and compare different fusion rules which can be used for Generalized Data Association (GDA)for multitarget tracking (MIT) in clutter. Most of tracking methods including Target Identification (ID) or attribute information are based on classical tracking algorithms as PDAF, JPDAF, MHT, IMM, etc and either on the Bayesian estimation and prediction of target ID, or on fusion of target class belief assignments through the Demspter-Shafer Theory (DST) and Dempster's rule ofcombination. In this paper we pursue ourprevious works on the development of a new GDA-M7T based o

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P., Sudha, and Murugan A. "Forest Fire Detection using Proportional Conflict Redistribution Rule2." September 10, 2018. https://doi.org/10.5281/zenodo.1412632.

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The objective of this paper is to detect fire in the forest where some plants and trees are prone to fire very easily. The detection of forest fire preserves economic and environmental wealth of forest and defends human life. Wireless Sensor Networks (WSNs) are used to monitor tactical and hazardous sites inside the forest.

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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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L., Mezai, and Hachouf F. "ADAPTIVE MULTIMODAL BIOMETRIC FUSION ALGORITHM USING PARTICLE SWARM OPTIMIZATION AND BELIEF FUNCTIONS." September 10, 2018. https://doi.org/10.5281/zenodo.1412397.

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In this paper, an adaptive multimodal biometric fusion algorithm is proposed. It is based on belief functions and Particle Swarm Optimization (PSO). The fusion is performed at the score level using belief functions such as Dempster Shafer, Yager, Proportional Conflict Redistribution and Dezert-Smarandache hybrid rules.

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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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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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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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29

Blasch, Erik, Jean Dezert, and P. Pannetier. "Overview of Dempster-Shafer and Belief Function Tracking Methods." July 1, 2015. https://doi.org/10.5281/zenodo.22621.

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Over the years, there have been many proposed methods in set-based tracking. One example of set-based methods is the use of Dempster-Shafer (DS) techniques to support belief-function (BF) tracking. In this paper, we overview the issues and concepts that motivated DS methods for simultaneous tracking and classification/identification. DS methods have some attributes, if applied correctly; but there are some pitfalls that need to be carefully avoided such as the redistribution of the mass associated with conflicting measurements. Such comparisons and applications are found in

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Jean, Dezert, Liu Zhun-ga, and Mercier Grégoire. "Edge Detection in Color Images Based on DSmT." July 1, 2015. https://doi.org/10.5281/zenodo.22458.

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In this paper, we present a non-supervised methodology for edge detection in color images based on belief functions and their combination. Our algorithm is based on the fusion of local edge detectors results expressed into basic belief assignments thanks to a flexible modeling, and the proportional conflict redistribution rule developed in DSmT framework. The application of this new belief-based edge detector is tested both on original (noise-free) Lena’s picture and on a modified image including artificial pixel noises to show the ability of our algori

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31

Jean, Dezert, Benameur Kaouthar, Ratton Laurent, and Grandin Jean-Francois. "On the Quality Estimation of Optimal Multiple Criteria Data Association Solutions." July 6, 2015. https://doi.org/10.5281/zenodo.34871.

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Abstract—In this paper, we present a method to estimate the quality (trustfulness) of the solutions of the classical optimal data association (DA) problem associated with a given source of information (also called a criterion). We also present a method to solve the multi-criteria DA problem and to estimate the quality of its solution. Our approach is new and mixes classical algorithms (typically Murty’s approach coupled with Auction) for the search of the best and the second best DA solutions, and belief functions (BF) with PCR6 (Proportional Conflict Redistribution rule # 6) combi

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32

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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Desmond, Adair, Emara-Shabaik Hosam, and Jaeger Martin. "Developing a monitoring system for long-distance pipeline leakage incorporating fusion of conflicting evidences." January 25, 2015. https://doi.org/10.5281/zenodo.22955.

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Quite often, during long-distance pipe leakage, critical decisions have to be made quickly and with as much certainty as possible using conflicting and uncertain sources of information. Key to providing quality decision options is an appropriate method of combining, or fusing, these heterogeneous evidence sources. Since the development of belief function theory introduced by Shafer in the 1970s many combination rules have been proposed in the literature because in highly conflicting situations the emblematic Dempster’s rule generates counterintuitive and una

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QiangGuo, He You, Jian Tao, Wang Haipeng, and Xia Shutao. "An evidence clustering DSmT approximate reasoning method for more than two sources." May 19, 2019. https://doi.org/10.5281/zenodo.2987095.

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Due to the huge computation complexity of Dezert–Smarandache Theory (DSmT), its applications especially for multi-source (more than two sources) complex fusion problems have been limited. To get high similar approximate reasoning results with Proportional Conflict Redistribution 6 (PCR6) rule in DSmT framework (DSmT +PCR6) and remain less computation complexity, an Evidence Clustering DSmT approximate reasoning method for more than two sources is proposed. Firstly, the focal elements of multi evidences are clustered to two sets by their mass assignments respectively. Secondly, the convex

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Nassim, Abbas, Chibani Youcef, Belhadi Zineb, and Hedir Mehdia. "A DSmT Based Combination Scheme for Multi-Class Classification." March 15, 2015. https://doi.org/10.5281/zenodo.22886.

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This paper presents a new combination scheme for reducing the number of focal elements to manipulate in order to reduce the complexity of the combination process in the multiclass framework. The basic idea consists in using of p sources of information involved in the global scheme providing p kinds of complementary information to feed each set of p one class support vector machine classifiers independently of each other, which are designed for detecting the outliers of the same target class, then, the outputs issued from this set of classifiers are 

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Erik, Blasch, Jøsang Audun, Dezert Jean, C. G. Costa Paulo, and Jousselme Anne-Laure. "URREF Self-Confidence in Information Fusion Trust." July 1, 2015. https://doi.org/10.5281/zenodo.22665.

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The Uncertainty Representation and Reasoning Evaluation Framework (URREF) includes an ontology that represents concepts and criteria needed to evaluate the uncertainty management aspects of a fusion system. The URREF ontology defines self-confidence as a measure of the information credibility as evaluated by the sensor itself. The concept of confidence, which is not explicitly defined in the ontology at URREF, has been extensively explored in the literature about evaluation in information fusion systems (IFS). In this paper, we provide a discussion on confidence&n

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Parodi, Marianela, and Juan C. Gómez. "Online Signature Verification: To What Extent Should a Classifier be Trusted in?" CLEI Electronic Journal 20, no. 2 (2017). http://dx.doi.org/10.19153/cleiej.20.2.5.

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To select the best features to model the signatures is one of the major challenges in the field of online signature verification. To combine different feature sets, selected by different criteria, is a useful technique to address this problem. In this line, the analysis of different features and their discriminative power has been researchers’ main concern, paying less attention to the way in which the different kind of features are combined. Moreover, the fact that conflicting results may appear when several classifiers are being used, has rarely been taken into account. In this paper, a scor

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