Relevant bibliographies by topics / Dempster’s fusion rule

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Dempster’s fusion rule'

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

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Journal articles on the topic "Dempster’s fusion rule"

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Jong, Myongnam, Yunhyok Paek, Hyonil Kim, and Cholsok Yu. "Analyzing the degree of conflict between bodies of evidence based on a new distance in data fusion." Advances in Data Science and Adaptive Analysis 13, no. 01 (2021): 2150004. http://dx.doi.org/10.1142/s2424922x21500042.

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Dempster’s combination rule may produce some unreasonable results when dealing with a combination of the conflicting evidence in evidence theory of Dempster–Shafer. Therefore, analyzing the degree of conflict between the bodies of evidence is essential to evaluate the applicability of Dempster’s rule. A new probability function, which is called a supporting probability function, is proposed to describe the correlation between evidences, and its distance is proposed to measure the distance between bodies of evidence. Combining this distance with classical conflict coefficient, a new method of e
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Bai, Shenshen, Longjie Li, and Xiaoyun Chen. "Conflicting evidence combination based on Belief Mover’s Distance." Journal of Intelligent & Fuzzy Systems 42, no. 3 (2022): 2005–21. http://dx.doi.org/10.3233/jifs-211397.

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The Dempster-Shafer evidence theory has been extensively used in various applications of information fusion owing to its capability in dealing with uncertain modeling and reasoning. However, when meeting highly conflicting evidence, the classical Dempster’s combination rule may give counter-intuitive results. To address this issue, we propose a new method in this work to fuse conflicting evidence. Firstly, a new evidence distance metric, named Belief Mover’s Distance, which is inspired by the Earth Mover’s Distance, is defined to measure the difference between two pieces of evidence. Subsequen
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Zhou, Ying, Yongchuan Tang, and Xiaozhe Zhao. "A Novel Uncertainty Management Approach for Air Combat Situation Assessment Based on Improved Belief Entropy." Entropy 21, no. 5 (2019): 495. http://dx.doi.org/10.3390/e21050495.

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Uncertain information exists in each procedure of an air combat situation assessment. To address this issue, this paper proposes an improved method to address the uncertain information fusion of air combat situation assessment in the Dempster–Shafer evidence theory (DST) framework. A better fusion result regarding the prediction of military intention can be helpful for decision-making in an air combat situation. To obtain a more accurate fusion result of situation assessment, an improved belief entropy (IBE) is applied to preprocess the uncertainty of situation assessment information. Data fus
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Tang, Yongchuan, Deyun Zhou, Zichang He, and Shuai Xu. "An improved belief entropy–based uncertainty management approach for sensor data fusion." International Journal of Distributed Sensor Networks 13, no. 7 (2017): 155014771771849. http://dx.doi.org/10.1177/1550147717718497.

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In real applications, sensors may work in complicated environments; thus, how to measure the uncertain degree of sensor reports before applying sensor data fusion is a big challenge. To address this issue, an improved belief entropy–based uncertainty management approach for sensor data fusion is proposed in this article. First, the sensor report is modeled as the body of evidence in Dempster–Shafer framework. Then, the uncertainty measure of each body of evidence is based on the subjective uncertainty represented as the evidence sufficiency and evidence importance, and the objective uncertaint
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Fan, Wentao, and Fuyuan Xiao. "A New Conflict Management in Evidence Theory Based on DEMATEL Method." Journal of Sensors 2019 (November 19, 2019): 1–12. http://dx.doi.org/10.1155/2019/7145373.

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D-S evidence theory is widely used in data fusion. However, the result of Dempster’s combination rule is not efficient and in highly conflicting situation. Though the existing methods have been proved efficient to deal with conflict in some applications, the indirect conflict among evidence is neglected to some degree. To solve this problem, a new method is proposed based on decision-making trial and evaluation laboratory (DEMATEL) and the belief correlation coefficient in this paper. The application in target recognition illustrates the efficiency of the proposed method. Compared with Dempste
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Klein, Lawrence A., Ping Yi, and Hualiang Teng. "Decision Support System for Advanced Traffic Management Through Data Fusion." Transportation Research Record: Journal of the Transportation Research Board 1804, no. 1 (2002): 173–78. http://dx.doi.org/10.3141/1804-23.

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The Dempster–Shafer theory for data fusion and mining in support of advanced traffic management is introduced and tested. Dempste–Shafer inference is a statistically based classification technique that can be applied to detect traffic events that affect normal traffic operations. It is useful when data or information sources contribute partial information about a scenario, and no single source provides a high probability of identifying the event responsible for the received information. The technique captures and combines whatever information is available from the data sources. Dempster’s rule
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Zhu, WenBo, Huicheng Yang, Yi Jin, and Bingyou Liu. "A Method for Recognizing Fatigue Driving Based on Dempster-Shafer Theory and Fuzzy Neural Network." Mathematical Problems in Engineering 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/6191035.

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This study proposes a method based on Dempster-Shafer theory (DST) and fuzzy neural network (FNN) to improve the reliability of recognizing fatigue driving. This method measures driving states using multifeature fusion. First, FNN is introduced to obtain the basic probability assignment (BPA) of each piece of evidence given the lack of a general solution to the definition of BPA function. Second, a modified algorithm that revises conflict evidence is proposed to reduce unreasonable fusion results when unreliable information exists. Finally, the recognition result is given according to the comb
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Elkosantini, Sabeur, and Ahmed Frikha. "Decision fusion for signalized intersection control." Kybernetes 44, no. 1 (2015): 57–76. http://dx.doi.org/10.1108/k-08-2013-0185.

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Purpose – Traffic congestion is becoming a serious problem that has adverse consequences on the socio-economy, environment, and public health of various cities worldwide. The purpose of this paper is to contribute to the continuous search for new alternative solutions to prevent or alleviate these concerns. It particularly deals with the development of decision support system based on a data fusion for the management and control of traffic at signalized intersections. The role of such systems is to manage the existing infrastructure to ease congestion and respond to crises. The proposed system
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Zhao, Yuxin, Hancong Feng, Kaili Jiang, and Bin Tang. "Information Fusion for Radar Signal Sorting with the Distributed Reconnaissance Receivers." Remote Sensing 15, no. 15 (2023): 3743. http://dx.doi.org/10.3390/rs15153743.

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The conventional method of centralizing information fusion is commonly employed for sorting radar signals in reconnaissance receivers. However, challenges arise when the distance between reconnaissance receivers and the fusion center is distant, or when the fusion center is compromised by hostile forces. To address these issues, this paper proposes a novel distributed information fusion method. In this method, each reconnaissance receiver is restricted to accessing adjacent nodes within an undirected graph for information transmission and local computation. The distributed Dempster’s combinati
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Deng, Zhan, and Jianyu Wang. "A Novel Evidence Conflict Measurement for Multi-Sensor Data Fusion Based on the Evidence Distance and Evidence Angle." Sensors 20, no. 2 (2020): 381. http://dx.doi.org/10.3390/s20020381.

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As an important method for uncertainty modeling, Dempster–Shafer (DS) evidence theory has been widely used in practical applications. However, the results turned out to be almost counter-intuitive when fusing the different sources of highly conflicting evidence with Dempster’s combination rule. In previous researches, most of them were mainly dependent on the conflict measurement method between the evidence represented by the evidence distance. However, it is inaccurate to characterize the evidence conflict only through the evidence distance. To address this issue, we comprehensively consider
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Dissertations / Theses on the topic "Dempster’s fusion rule"

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Tan, Heng Chuan. "Vers des communications de confiance et sécurisées dans un environnement véhiculaire." Thesis, Paris, ENST, 2017. http://www.theses.fr/2017ENST0063/document.

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Le routage et la gestion des clés sont les plus grands défis dans les réseaux de véhicules. Un comportement de routage inapproprié peut affecter l’efficacité des communications et affecter la livraison des applications liées à la sécurité. D’autre part, la gestion des clés, en particulier en raison de l’utilisation de la gestion des certificats PKI, peut entraîner une latence élevée, ce qui peut ne pas convenir à de nombreuses applications critiques. Pour cette raison, nous proposons deux modèles de confiance pour aider le protocole de routage à sélectionner un chemin de bout en bout sécurisé
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Tan, Heng Chuan. "Vers des communications de confiance et sécurisées dans un environnement véhiculaire." Electronic Thesis or Diss., Paris, ENST, 2017. http://www.theses.fr/2017ENST0063.

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Le routage et la gestion des clés sont les plus grands défis dans les réseaux de véhicules. Un comportement de routage inapproprié peut affecter l’efficacité des communications et affecter la livraison des applications liées à la sécurité. D’autre part, la gestion des clés, en particulier en raison de l’utilisation de la gestion des certificats PKI, peut entraîner une latence élevée, ce qui peut ne pas convenir à de nombreuses applications critiques. Pour cette raison, nous proposons deux modèles de confiance pour aider le protocole de routage à sélectionner un chemin de bout en bout sécurisé
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Jiao, Lianmeng. "Classification of uncertain data in the framework of belief functions : nearest-neighbor-based and rule-based approaches." Thesis, Compiègne, 2015. http://www.theses.fr/2015COMP2222/document.

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Dans de nombreux problèmes de classification, les données sont intrinsèquement incertaines. Les données d’apprentissage disponibles peuvent être imprécises, incomplètes, ou même peu fiables. En outre, des connaissances spécialisées partielles qui caractérisent le problème de classification peuvent également être disponibles. Ces différents types d’incertitude posent de grands défis pour la conception de classifieurs. La théorie des fonctions de croyance fournit un cadre rigoureux et élégant pour la représentation et la combinaison d’une grande variété d’informations incertaines. Dans cette thè
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Book chapters on the topic "Dempster’s fusion rule"

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Guyard, Romain, and Véronique Cherfaoui. "Study of Distributed Data Fusion Using Dempster’s Rule and Cautious Operator." In Belief Functions: Theory and Applications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99383-6_13.

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Palmieri Francesco and Ciuonzo Domenico. "Data Fusion with Entropic Priors." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2011. https://doi.org/10.3233/978-1-60750-692-8-107.

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In classification problems, lack of knowledge of the prior distribution may make the application of Bayes' rule inadequate. Uniform or arbitrary priors may often provide classification answers that, even in simple examples, may end up contradicting our common sense about the problem. Entropic priors, determined via the application of the maximum entropy principle, seem to provide a much better answer and can be easily derived and applied to classification tasks when no more than the likelihood functions are available. In this paper we present an example in which the use of the entropic priors
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Conference papers on the topic "Dempster’s fusion rule"

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Roggemann, Michael C., James P. Mills, Steven K. Rogers, and Matthew Kabrisky. "Features and information fusion in multiple sensor object recognition." In OSA Annual Meeting. Optica Publishing Group, 1988. http://dx.doi.org/10.1364/oam.1988.mb5.

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Automatic pattern recognition using multiple sensors offers a promising approach to many pattern recognition problems. Among the many research issues which remain are determination and extraction of useful information from the imagery and fusion of the information derived from multiple sources. The technique being investigated applies the Dempster-Shafer theory of evidence1 to information in the form of features extracted from multiple sensor views of a scene. Features are extracted from segmented regions of a database of real corresonding IR and absolute range images. Multiple sensor features
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Haenni, Rolf. "Uncover Dempster's Rule Where It Is Hidden." In 2006 9th International Conference on Information Fusion. IEEE, 2006. http://dx.doi.org/10.1109/icif.2006.301675.

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Haenni, R. "Shedding new light on Zadeh's criticism of Dempster's rule of combination." In 2005 7th International Conference on Information Fusion. IEEE, 2005. http://dx.doi.org/10.1109/icif.2005.1591951.

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Dezert, Jean, Albena Tchamova, Florentin Smarandache, and Pavlina Konstantinova. "Target Type Tracking with PCR5 and Dempster's rules: A Comparative Analysis." In 2006 9th International Conference on Information Fusion. IEEE, 2006. http://dx.doi.org/10.1109/icif.2006.301556.

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Li, Yingchun, Wei Xiong, Desheng Liu, and JianBo Cheng. "A New Preprocessing Method on Evidence Weight of Dempster Fusion Rule." In 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017). Atlantis Press, 2017. http://dx.doi.org/10.2991/fmsmt-17.2017.240.

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Tabib, Ramesh Ashok, Ujwala Patil, Syed Altaf Ganihar, Neeta Trivedi, and Uma Mudenagudi. "Decision fusion for robust horizon estimation using Dempster Shafer Combination Rule." In 2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG). IEEE, 2013. http://dx.doi.org/10.1109/ncvpripg.2013.6776247.

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Ren, Jinshen, Botao Jiang, and Fuyu Zhao. "Simultaneous Fault Diagnosis of the Reactor Coolant System Based on the DSM Evidence Theory." In 2013 21st International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/icone21-16209.

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Fault diagnosis of nuclear power plant (NPP) has become a major research topic in ensuring the reliability and safety for the NPP operation. In the light of complexity and information uncertainty of nuclear reactor coolant system, some diagnosis techniques based on the multi-sensor information fusion theories have been widely used. As one part of the those theories, the Dempster-Shafer (D-S) theory excelled in demonstrating and combining uncertain information has witnessed a wide range of applications in the fault diagnosis fields. It can be inferred from the previous studies that the fault di
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