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Relevant bibliographies by topics / Hybrid Dezert-Smarandache theory

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Academic literature on the topic 'Hybrid Dezert-Smarandache theory'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Hybrid Dezert-Smarandache theory"

1

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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2

Xian, LI, CHEN Zhigang, and JING Peiliang. "DSmH Evidential Network for Target Identication." April 1, 2015. https://doi.org/10.5281/zenodo.22912.

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p>This paper proposes a model of evidential network based on Hybrid Dezert-Smarandache theory (DSmH)br /> to improve target identi cation of multi-sensors. In the classi cation simulation, we compared thebr /> results obtained at the Target Type node and Foe-Ally node in evidential network by using Dempster-br /> Shafer theory (DS) and using DSmH. The comparisons show that, when we use DSmH in the evidentialbr /> network, we can assign more Basic Belief Assignments (BBA) to the focal element the target belongs to.br /> Experiments con rm that the model of evidential network u

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3

Azeddine, Elhassouny, Idbraim Soufiane, Bekkari Aissam, Mammass Driss, and Ducrot Danielle. "Change Detection by Fusion/Contextual Classification based on a Hybrid DSmT Model and ICM with Constraints." December 11, 2011. https://doi.org/10.5281/zenodo.22914.

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The Dezert - Smarandache Theory (DSmT) used for the fusion and the modeling of the classes sets of themes has shown its performances in the detection and the cartography of the changes. Moreover the contextual classification with the research for the optimal solution by an ICM (Iterated conditional mode) algorithm with constraints allows to take in account the parcellary aspect of the thematic classes, thus, the introduction of this contextual information in the fusion process has enabled us to better identify the topics of surface and the detection of the changes.

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4

Xian, LI, CHEN Zhigang, and JING Peiliang. "DSmH Evidential Network for Target Identication." August 17, 2015. https://doi.org/10.5281/zenodo.32214.

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p>This paper proposes a model of evidential network based on Hybrid Dezert-Smarandache theory (DSmH)br /> to improve target identi cation of multi-sensors. In the classi cation simulation, we compared thebr /> results obtained at the Target Type node and Foe-Ally node in evidential network by using Dempster-br /> Shafer theory (DS) and using DSmH. The comparisons show that, when we use DSmH in the evidentialbr /> network, we can assign more Basic Belief Assignments (BBA) to the focal element the target belongs to.br /> Experiments con rm that the model of evidential network u

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5

Pascal, Djiknavorian, Valin Pierre, and Grenier Dominic. "Implementation of Approximations of Belief Functions for Fusion of ESM Reports within the DSm Framework." July 1, 2015. https://doi.org/10.5281/zenodo.22483.

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Electronic Support Measures consist of passive receivers which can identify emitters which, in turn, can be related to platforms that belong to 3 classes: Friend, Neutral, or Hostile. Decision makers prefer results presented in STANAG 1241 allegiance form, which adds 2 new classes: Assumed Friend, and Suspect. Dezert-Smarandache (DSm) theory is particularly suited to this problem, since it allows for intersections between the original 3 classes. However, as we know, the DSm hybrid combination rule is highly complex to execute and requires high amounts of reso

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6

Xinde, Li, Huang Xinhan, and Wang Min. "Robot Map Building from Sonar and Laser Information using DSmT with Discounting Theory." International Journal of Mechanical, Industrial and Aerospace Sciences 0.0, no. 7 (2007). https://doi.org/10.5281/zenodo.1331353.

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In this paper, a new method of information fusion – DSmT (Dezert and Smarandache Theory) is introduced to apply to managing and dealing with the uncertain information from robot map building. Here we build grid map form sonar sensors and laser range finder (LRF). The uncertainty mainly comes from sonar sensors and LRF. Aiming to the uncertainty in static environment, we propose Classic DSm (DSmC) model for sonar sensors and laser range finder, and construct the general basic belief assignment function (gbbaf) respectively. Generally speaking, the evidence sources are unreliable in physic

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