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Journal articles on the topic 'Extended Dempster Shafer theory'

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Published: 4 June 2025

Last updated: 1 August 2025

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1

Li, Jin Gang, Chun Na Zheng, Hong Wei Xuan, and Yan Jiang. "Data Fusion in Environment Monitoring Systems with Extended Dempster-Shafer Theory." Applied Mechanics and Materials 543-547 (March 2014): 1074–77. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.1074.

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In order to improve the accuracy and reliability of multi-source heterogeneous data in the collection process for environment monitoring, according to the analysis of the limitations, the existing methods and the features of data collected, a new kind of data fusion approach based on extended Dempster-Shafer theory is proposed. The mathematical description of extended Dempster-Shafer theory based on the data fusion is defined and the corresponding model is developed in which the data fusion method and the implementation of the algorithm are discussed. Finally, the proposed approach is applied

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Jia, Zhuosheng, Yingjun Zhang, and Xuemin Dong. "An Extended Intuitionistic Fuzzy Cognitive Map via Dempster-Shafer Theory." IEEE Access 8 (2020): 23186–96. http://dx.doi.org/10.1109/access.2020.2970159.

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E. Farmer, Michael. "Human Cognitive Models for Heritage Site Monitoring." Digital Presentation and Preservation of Cultural and Scientific Heritage 11 (September 10, 2021): 19–32. http://dx.doi.org/10.55630/dipp.2021.11.1.

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Integrating evidence from a single sensor over time is becoming more common due to the Internet of Things (IoT). It can play a critical role in Heritage site monitoring, as networks of sensors are required to catalog and analyze data over extended periods of time. Researchers have often adopted the mechanisms used for multi-source integration, such as Bayesian conditioning and Dempster- Shafer reasoning. Research in human cognitive models provides an interesting alternative insights for accumulating evidence over time. We used this research as a foundation for the current approach which integr

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Vinothiyalakshmi, P., and R. Anitha. "Workload Mining in Cloud Computing using Extended Cloud Dempster–Shafer Theory (ECDST)." Wireless Personal Communications 114, no. 1 (2020): 389–407. http://dx.doi.org/10.1007/s11277-020-07368-1.

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LIU, WEIRU, JUN HONG, M. F. McTEAR, and J. G. HUGHES. "AN EXTENDED FRAMEWORK FOR EVIDENTIAL REASONING SYSTEMS." International Journal of Pattern Recognition and Artificial Intelligence 07, no. 03 (1993): 441–57. http://dx.doi.org/10.1142/s0218001493000224.

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Use of the Dempster-Shafer (D-S) theory of evidence to deal with uncertainty in knowledge-based systems has been widely addressed. Several AI implementations have been undertaken based on the D-S theory of evidence or the extended theory. But the representation of uncertain relationships between evidence and hypothesis groups (heuristic knowledge) is still a major problem. This paper presents an approach to representing such knowledge, in which Yen’s probabilistic multi-set mappings have been extended to evidential mappings, and Shafer’s partition technique is used to get the mass function in

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Jiang, Wen, Jun Zhan, Deyun Zhou, and Xin Li. "A Method to Determine Generalized Basic Probability Assignment in the Open World." Mathematical Problems in Engineering 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/3878634.

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Dempster-Shafer evidence theory (D-S theory) has been widely used in many information fusion systems since it was proposed by Dempster and extended by Shafer. However, how to determine the basic probability assignment (BPA), which is the main and first step in D-S theory, is still an open issue, especially when the given environment is in an open world, which means the frame of discernment is incomplete. In this paper, a method to determine generalized basic probability assignment in an open world is proposed. Frame of discernment in an open world is established first, and then the triangular

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Porebski, Sebastian, Piotr Porwik, Ewa Straszecka, and Tomasz Orczyk. "Liver fibrosis diagnosis support using the Dempster–Shafer theory extended for fuzzy focal elements." Engineering Applications of Artificial Intelligence 76 (November 2018): 67–79. http://dx.doi.org/10.1016/j.engappai.2018.09.004.

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Fei, Liguo, Jun Xia, Yuqiang Feng, and Luning Liu. "A novel method to determine basic probability assignment in Dempster–Shafer theory and its application in multi-sensor information fusion." International Journal of Distributed Sensor Networks 15, no. 7 (2019): 155014771986587. http://dx.doi.org/10.1177/1550147719865876.

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Multi-sensor information fusion occurs in a vast variety of applications, including medical diagnosis, automatic drive, speech recognition, and so on. Often these problems can be modeled by Dempster–Shafer theory. In Dempster–Shafer theory, the most primary processing unit is the basic probability assignment, which is a description of objective information in the real world. How to make this description more effective is a vital but open issue. A novel basic probability assignment generation model is proposed in this article whose objective is to provide perspective with respect to how basic p

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Fei, Liguo, and Yuqiang Feng. "Modeling Interactive Multiattribute Decision-Making via Probabilistic Linguistic Term Set Extended by Dempster–Shafer Theory." International Journal of Fuzzy Systems 23, no. 2 (2021): 599–613. http://dx.doi.org/10.1007/s40815-020-01019-0.

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Aminravan, Farzad, Rehan Sadiq, Mina Hoorfar, Manuel J. Rodriguez, Alex Francisque, and Homayoun Najjaran. "Evidential reasoning using extended fuzzy Dempster-Shafer theory for handling various facets of information deficiency." International Journal of Intelligent Systems 26, no. 8 (2011): 731–58. http://dx.doi.org/10.1002/int.20491.

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Gan, Dingyi, Bin Yang, and Yongchuan Tang. "An Extended Base Belief Function in Dempster–Shafer Evidence Theory and Its Application in Conflict Data Fusion." Mathematics 8, no. 12 (2020): 2137. http://dx.doi.org/10.3390/math8122137.

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The Dempster–Shafer evidence theory has been widely applied in the field of information fusion. However, when the collected evidence data are highly conflicting, the Dempster combination rule (DCR) fails to produce intuitive results most of the time. In order to solve this problem, the base belief function is proposed to modify the basic probability assignment (BPA) in the exhaustive frame of discernment (FOD). However, in the non-exhaustive FOD, the mass function value of the empty set is nonzero, which makes the base belief function no longer applicable. In this paper, considering the influe

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Wang, Xiao Bo, Fan Zhao, Xiao Li, and Rong Hui Zhang. "Cross Language Query Expansion Approach for CIMS Based on Weighted D-S Evidence Theory." Key Engineering Materials 620 (August 2014): 534–43. http://dx.doi.org/10.4028/www.scientific.net/kem.620.534.

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With the Computer Integrated Manufacturing System and Information Technology rapid development, rapid retrieval multilingual becomes one of the hot spots in Machine Translation. The cross-language information retrieval (CLIR) provides a convenient way, enabling users to use their own familiar language to submit queries to retrieve documents in another language. Basic query expansion is one of the effective methods to improve recall of information retrieval. There are many researchers have proposed many extension methods, but most methods are simply added to the query expansion terms. If we do

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Leung, Yee, Rongrong Li, and Nannan Ji. "Application of extended Dempster–Shafer theory of evidence in accident probability estimation for dangerous goods transportation." Journal of Geographical Systems 19, no. 3 (2017): 249–71. http://dx.doi.org/10.1007/s10109-017-0253-2.

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Devi, Rashmi Rekha, and Surajit Chattopadhyay. "An Interpretation of the Surface Temperature Time Series through Fuzzy Measures." Axioms 12, no. 5 (2023): 475. http://dx.doi.org/10.3390/axioms12050475.

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This paper reports a study to interpret the surface temperature based on time series and fuzzy measures. We demonstrated a method to identify the uncertainty around the surface temperature data concerning the summer monsoon in India. The random variables were standardized, and the Dempster-Shafer Theory was used to generate common goals. Two criteria, represented as fuzzy numbers, were used for this purpose. We constructed three polynomials to illustrate a functional connection between time series and the measure of joint belief. The analysis of the obtained results showed that the certainty i

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Porębski, Sebastian, and Ewa Straszecka. "Membership Functions for Fuzzy Focal Elements." Archives of Control Sciences 26, no. 3 (2016): 395–427. http://dx.doi.org/10.1515/acsc-2016-0022.

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Abstract The paper presents a study on data-driven diagnostic rules, which are easy to interpret by human experts. To this end, the Dempster-Shafer theory extended for fuzzy focal elements is used. Premises of the rules (fuzzy focal elements) are provided by membership functions which shapes are changing according to input symptoms. The main aim of the present study is to evaluate common membership function shapes and to introduce a rule elimination algorithm. Proposed methods are first illustrated with the popular Iris data set. Next experiments with five medical benchmark databases are perfo

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A.Priyadharshini. "A Survey of Security Issues in MANET." RESEARCH REVIEW International Journal of Multidisciplinary 3, no. 12 (2018): 357–60. https://doi.org/10.5281/zenodo.2456305.

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Mobile Ad hoc Networks are widely used in defense applications where traditional wireless network is difficult to implement as the network is formed by autonomous and decentralized wireless nodes. Privacy and Security in MANET are the most important disquiet for basic functionality of the network. Security is the major challenge in MANETs because of its characteristics like resource constraints, open medium, lack of fixed infrastructure, dynamism of topology and no clear security mechanism. As the topology is dynamic, routing process is very difficult. So MANET often suffers from routing attac

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Sezer, Sukru Ilke, Emre Akyuz, and Ozcan Arslan. "An extended HEART Dempster–Shafer evidence theory approach to assess human reliability for the gas freeing process on chemical tankers." Reliability Engineering & System Safety 220 (April 2022): 108275. http://dx.doi.org/10.1016/j.ress.2021.108275.

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Hussain, Shahid, Zahid Hussain, Rashid Hussain, et al. "A Novel Framework for Belief and Plausibility Measures in Intuitionistic Fuzzy Sets: Belief and Plausibility Distance, Similarity, and TOPSIS for Multicriteria Decision Making." Axioms 13, no. 12 (2024): 858. https://doi.org/10.3390/axioms13120858.

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Dempster–Shafer Theory (DST) relies significantly on belief and plausibility measures to handle ambiguity and uncertainty; however, DST has been extended to fuzzy sets (FSs) and intuitionistic fuzzy sets (IFSs) with only a few extensions focusing on belief and plausibility intuitionistic fuzzy distance (BP-distance) and similarity (BP-similarity) until now. In this work, we propose a novel framework for the belief and plausibility of intuitionistic fuzzy sets (BP-IFSs) and their BP-distance and BP-similarity measures. We modified steps 4 and 5 of the classical TOPSIS method, utilizing both dis

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Li, Jiali, Shengjing Tang, and Jie Guo. "Noise-Adaption Extended Kalman Filter Based on Deep Deterministic Policy Gradient for Maneuvering Targets." Sensors 22, no. 14 (2022): 5389. http://dx.doi.org/10.3390/s22145389.

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Although there have been numerous studies on maneuvering target tracking, few studies have focused on the distinction between unknown maneuvers and inaccurate measurements, leading to low accuracy, poor robustness, or even divergence. To this end, a noise-adaption extended Kalman filter is proposed to track maneuvering targets with multiple synchronous sensors. This filter avoids the simultaneous adjustment of the process model and measurement model without distinction. Instead, the maneuver detection based on the Dempster-Shafer evidence theory is constructed to achieve the reliable distincti

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Ramezani, S., A. Moini, M. Riahi, and A. C. Marquez. "Predicting the remaining useful life in the presence of the regime-switching behaviour of health index using distance-based evidence theory." Insight - Non-Destructive Testing and Condition Monitoring 63, no. 1 (2021): 37–46. http://dx.doi.org/10.1784/insi.2021.63.1.37.

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With the development of new maintenance techniques based on condition monitoring, diagnostic and prognostic methods are also being extended. In the process of estimating the remaining useful life (RUL) using the data-driven approach, it is difficult to determine the degradation state of the equipment with several sources of information and to predict the remaining useful life with non-smooth data that have sudden changes inherent in the monitoring data. In this paper, a procedure is presented to address these two issues in which the degradation state of the equipment is determined in the prese

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Han, Youkyung, Aisha Javed, Sejung Jung, and Sicong Liu. "Object-Based Change Detection of Very High Resolution Images by Fusing Pixel-Based Change Detection Results Using Weighted Dempster–Shafer Theory." Remote Sensing 12, no. 6 (2020): 983. http://dx.doi.org/10.3390/rs12060983.

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Change detection (CD), one of the primary applications of multi-temporal satellite images, is the process of identifying changes in the Earth’s surface occurring over a period of time using images of the same geographic area on different dates. CD is divided into pixel-based change detection (PBCD) and object-based change detection (OBCD). Although PBCD is more popular due to its simple algorithms and relatively easy quantitative analysis, applying this method in very high resolution (VHR) images often results in misdetection or noise. Because of this, researchers have focused on extending the

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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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Seraj, Sahand, and Mahmoud Reza Delavar. "An extended GIS-based Dempster–Shafer theory for play-based hydrocarbon exploration risk analysis under spatial uncertainty conditions, case study: Zagros sedimentary basin, Iran." Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards 13, no. 2 (2018): 131–44. http://dx.doi.org/10.1080/17499518.2018.1532522.

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Bu, Liangtao, and Hui Yue. "Quality Risk Perception of Rectification and Reinforcement in a High-Rise Building under Uncertainty." Buildings 14, no. 3 (2024): 774. http://dx.doi.org/10.3390/buildings14030774.

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There are many complex and uncertain factors in the process of building rectification and reinforcement that can easily lead to construction quality failures. This study develops a novel hybrid risk analysis approach to perceive the construction quality risk under uncertainty by integrating the extension theory (ET), the cloud model (CM), the Dempster–Shafer (D-S) evidence theory and the dynamic Bayesian network (DBN). The extended cloud model (ECM) combining the ET and the CM is not only effective in avoiding information loss, but is also capable of dealing with the ambiguity and randomness i

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Xu, Shijun, Yi Hou, Xinpu Deng, Peibo Chen, and Shilin Zhou. "Determination of Evidence Weights Based on Convolutional Neural Network for Classification Problem." Journal of Sensors 2022 (September 29, 2022): 1–8. http://dx.doi.org/10.1155/2022/1616401.

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The weighted average is an efficient way to address conflicting evidence combination in the Dempster-Shafer evidence theory. However, it is an open issue how to determine the evidence weights reasonably. Although many traditional conflicting evidence combination solutions based on evidence distance or entropy have been put forward, the evidence weights are determined with a single aspect, and no comprehensive consideration of other useful information affects the weights. Thus, it does not ensure that determination of weights is the most reasonable. By introducing deep learning into conflicting

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Khanuja, Harmeet Kaur, and Dr D. S. Adane. "Forensic Analysis of Databases by Combining Multiple Evidences." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 7, no. 3 (2013): 654–63. http://dx.doi.org/10.24297/ijct.v7i3.3446.

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The information security for securing enterprise databases from internal and external attacks and violations of mutual policy is an interminable struggle. With the growing number of attacks and frauds, the organizations are finding it difficult to meet various regulatory compliance requirements such as SOX, HIPAA, and state privacy laws. The aim here is to develop a methodology which monitors the database transactions on continuous basis and to make a decision whether the database transactions are legitimate or suspicious by combining multiple evidences gathered. The suspicious transactions ca

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Skowron, Andrzej. "The Rough Sets Theory and Evidence Theory." Fundamenta Informaticae 13, no. 3 (1990): 245–62. http://dx.doi.org/10.3233/fi-1990-13303.

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The aim of the paper is to show some connections between the rough sets theory and the Dempser-Shafer approach. We prove that for every Pawlak’s approximation space there exists a Dempster-Shafer space with the qualities of the lower and upper approximations of sets in the approximation space equal to the credibility and plausibility of sets in the Dempster-Shafer space, respectively. Analogous connections hold between approximation spaces generated by the decision tables and Dempster-Shafer spaces, namely for every decision table space there exists a Dempster-Shafer space such that the qualit

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Mu, Kedian. "Symbolic Dempster-Shafer Theory." Journal of Computer Research and Development 42, no. 11 (2005): 1833. http://dx.doi.org/10.1360/crad20051101.

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Azimirad, Ehsan, and Seyyed Reza Movahhed Ghodsinya. "The improvement of uncertainty measurements accuracy in sensor networks based on fuzzy dempster-shafer theory." International Journal of Advances in Intelligent Informatics 6, no. 2 (2020): 149. http://dx.doi.org/10.26555/ijain.v6i2.461.

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Threat Assessment is one of the most important components in combat management systems. However, uncertainty is one of the problems that occur in the input data of these systems that have been provided using several sensors in sensor networks. In literature, there are some theories that state and model uncertainty in the information. One of the new methods is the Fuzzy Dempster-Shafer Theory. In this paper, a model-based uncertainty is presented in the air defense system based on the Fuzzy Dempster-Shafer Theory to measure uncertainty and its accuracy. This model uses the two concepts naming o

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RAKOWSKY, UWE KAY. "FUNDAMENTALS OF THE DEMPSTER-SHAFER THEORY AND ITS APPLICATIONS TO RELIABILITY MODELING." International Journal of Reliability, Quality and Safety Engineering 14, no. 06 (2007): 579–601. http://dx.doi.org/10.1142/s0218539307002817.

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The Dempster-Shafter Theory is well-known for its usefulness to express uncertain judgments of experts. This contribution shows how to apply the calculus to safety and reliability modeling, especially to expert judgment; Failure Modes, Effects, and Criticality Analysis; Event Tree Analysis, Fault Tree Analysis, and Reliability Centered Maintenance. Including a tutorial introduction to the Dempster-Shafer Theory, the differences between the Probability and the Dempster-Shafer Theory are discussed widely.

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Wang, Yanxue, Fang Liu, and Aihua Zhu. "Bearing Fault Diagnosis Based on a Hybrid Classifier Ensemble Approach and the Improved Dempster-Shafer Theory." Sensors 19, no. 9 (2019): 2097. http://dx.doi.org/10.3390/s19092097.

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Bearing fault diagnosis of a rotating machine plays an important role in reliable operation. A novel intelligent fault diagnosis method for roller bearings has been developed based on a proposed hybrid classifier ensemble approach and the improved Dempster-Shafer theory. The improved Dempster-Shafer theory well considered the combination of unreliable evidence sources, the uncertainty information of basic probability assignment, and the relative credibility of the evidence on the weights in the process of decision making under the framework of fuzzy preference relations, which can effectively

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Qu, Hong Chun, Xie Bin Ding, and Tai Yong Wang. "Aeroengine Oil Fault Diagnosis Based on D-S Evidential Theory." Applied Mechanics and Materials 141 (November 2011): 15–20. http://dx.doi.org/10.4028/www.scientific.net/amm.141.15.

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Aeroengine oil contains wear debris generated by friction. Based on the Dempster-Shafer evidence combination theory, aeroengine wear conditions can be effectively diagnosed. Through analysising the elements of wear debris in lubricating meduim, it can determine engines wear levels and wear parts, as references for troubleshooting. In the process of combination, an method was proposed that every element of wear quantity and wear rate were fused at first,then the integration of all elements. For Dempster-Shafer has its own limitations, two impoved methods were applied to and were compared. The r

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Maseleno, Andino, Md Mahmud Hasan, and Norjaidi Tuah. "Combining Fuzzy Logic and Dempster-Shafer Theory." TELKOMNIKA Indonesian Journal of Electrical Engineering 16, no. 3 (2015): 583. http://dx.doi.org/10.11591/tijee.v16i3.1651.

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This research aims to combine the mathematical theory of evidence with the rule based logics to refine the predictable output. Integrating Fuzzy Logic and Dempster-Shafer theory by calculating the similarity between Fuzzy membership function. The novelty aspect of this work is that basic probability assignment is proposed based on the similarity measure between membership function. The similarity between Fuzzy membership function is calculated to get a basic probability assignment. The Dempster-Shafer mathematical theory of evidence has attracted considerable attention as a promising method of

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Wahyuni, Elyza Gustri, and Widodo Prijodiprodjo. "Prototype Sistem Pakar untuk Mendeteksi Tingkat Resiko Penyakit Jantung Koroner dengan Metode Dempster-Shafer." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 7, no. 2 (2013): 133. http://dx.doi.org/10.22146/ijccs.3352.

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AbstrakSistem pakar dapat berfungsi sebagai konsultan yang memberi saran kepada pengguna sekaligus sebagai asisten bagi pakar. Salah satu cara untuk mengatasi dan membantu mendeteksi tingkat resiko penyakit JK seseorang, yaitu dengan membuat sebuah sistem pakar sebagai media konsultasi dan monitoring terhadap seseorang sehingga dapat meminimalkan terjadinya serangan jantung yang mengakibatkan kematian. Metode Dempster-Shafer merupakan metode penalaran non monotonis yang digunakan untuk mencari ketidakkonsistenan akibat adanya penambahan maupun pengurangan fakta baru yang akan merubah aturan ya

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Jia, Li, Hai Yan, Guo Hui Li, and Hui Zhang. "Target Classification Using PAS and Evidence Theory." Applied Mechanics and Materials 347-350 (August 2013): 3728–33. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.3728.

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This paper presents a novel Dempster-Shafer evidence construction approach for aircraft aim recognition. The prior-probability of the properties of aircraft was used for establishing a probabilistic argumentation system. Dempster-Shafer evidence was constructed by assumption-based reasoning. Therefore, additional information could be provided to the classification of the data fusion system. Experiments on artificial and real data demonstrated that the proposed method could improve the classification results.

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Azhari, M. Faishal, and Raissa Amanda Putri. "Application of Dempster-Shafer Theory Method in Expert System for Diagnosis of Psychological Disorders in Children." Brilliance: Research of Artificial Intelligence 4, no. 1 (2024): 81–93. http://dx.doi.org/10.47709/brilliance.v4i1.3764.

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The development of technology at this time has changed very rapidly in recent decades. Expert system is one of the sub-sections of artificial intelligence that aims to process and display the results of the conclusion of the previous process based on the knowledge that has been obtained. The purpose of this research is to apply the Dempster-Shafer method to the expert system for diagnosing psychological disorders in children and to design and build an expert system using the Dempster-Shafer method on a website-based expert system for diagnosing psychological disorders in children. Based on the

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Wang, Xin, Ying Wang, and Hongbin Sun. "Exploring the Combination of Dempster-Shafer Theory and Neural Network for Predicting Trust and Distrust." Computational Intelligence and Neuroscience 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/5403105.

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In social media, trust and distrust among users are important factors in helping users make decisions, dissect information, and receive recommendations. However, the sparsity and imbalance of social relations bring great difficulties and challenges in predicting trust and distrust. Meanwhile, there are numerous inducing factors to determine trust and distrust relations. The relationship among inducing factors may be dependency, independence, and conflicting. Dempster-Shafer theory and neural network are effective and efficient strategies to deal with these difficulties and challenges. In this

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Zhang, Qian, Zhi Liu, Zhilan Zhang, et al. "Research on the Circuit Breaker State Judgment Method Based on Ant Colony Optimization Dempster-Shafer Evidence Theory." Computation 13, no. 2 (2025): 43. https://doi.org/10.3390/computation13020043.

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The paper proposes a method for circuit breaker state judgment based on ant colony algorithm-optimized Dempster-Shafer evidence theory.It can improve the accuracy and robustness of state judgment. As a key device in the power system, the state judgment of circuit breakers is crucial for the safety and stability of the power grid. Existing methods have limitations in handling conflicts and uncertainties of multi-source data, and a single model is difficult to meet the needs of complex data fusion. Therefore, the paper applies the ant colony algorithm to optimize the basic probability assignment

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V.A, Phuke, and H. N. Bharathi. "Information Retrieval using Dempster-Shafer Theory." International Journal of Computer Applications 102, no. 13 (2014): 33–37. http://dx.doi.org/10.5120/17879-8876.

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MONNEY, PAUL-ANDRE, and MOSES CHAN. "MODELLING DEPENDENCE IN DEMPSTER-SHAFER THEORY." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 15, no. 01 (2007): 93–114. http://dx.doi.org/10.1142/s021848850700439x.

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Belief functions can only be combined by Dempster's rule when they are based on independent items of evidence. This paper proposes a method for handling the case where there is some probabilistic dependence among the items of evidence. The method relies on compact representations of joint probability distributions on the assumption variables associated with the belief functions. These distributions are then used to compute degrees of support of hypotheses of interest. It is shown that the theory of hints is the appropriate general framework for this method.

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Siemiątkowska, Barbara, and Bogdan Harasymowicz-Boggio. "Place Classification using Dempster-Shafer Theory." Foundations of Computing and Decision Sciences 42, no. 3 (2017): 257–73. http://dx.doi.org/10.1515/fcds-2017-0013.

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AbstractThe paper presents a novel place labeling method. It is assumed that an indoor mobile robot equipped with a camera or RGB-D sensor ambulates an indoor environment. The places visited by the robot are classified based on objects which have been recognized. Each object (or set of objects) votes for a set of room classes. Data aggregation is performed using Dempster-Shafer theory (DST), which can be regarded as a generalization of the Bayesian theory. The possibility of taking into account the uncertainty of data is the main advantage of the described method. The classic Dempster’s rule o

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Denœux, Thierry. "40 years of Dempster–Shafer theory." International Journal of Approximate Reasoning 79 (December 2016): 1–6. http://dx.doi.org/10.1016/j.ijar.2016.07.010.

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HAJEK, P., and D. HARMANEC. "AN EXERCISE IN DEMPSTER-SHAFER THEORY." International Journal of General Systems 20, no. 2 (1992): 137–42. http://dx.doi.org/10.1080/03081079208945023.

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Elmore, Paul A., Frederick E. Petry, and Ronald R. Yager. "Geospatial Modeling Using Dempster–Shafer Theory." IEEE Transactions on Cybernetics 47, no. 6 (2017): 1551–61. http://dx.doi.org/10.1109/tcyb.2016.2551979.

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Roesmer, Christopher. "Nonstandard analysis and Dempster-Shafer theory." International Journal of Intelligent Systems 15, no. 2 (2000): 117–27. http://dx.doi.org/10.1002/(sici)1098-111x(200002)15:2<117::aid-int2>3.0.co;2-2.

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Mukherjee, Chiranjib, and Gyan Mukherjee. "DEMPSTER-SHAFER THEORY BY PROBABILISTIC REASONING." COMPUSOFT: An International Journal of Advanced Computer Technology 03, no. 09 (2014): 1083–86. https://doi.org/10.5281/zenodo.14752184.

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Probabilistic reasoning is used when outcomes are unpredictable. We examine the methods which use probabilistic representations for all knowledge and which reason by propagating the uncertainties can arise from evidence and assertions to conclusions. The uncertainties can arise from an inability to predict outcomes due to unreliable, vague, in complete or inconsistent knowledge. Some approaches taken in Artificial Intelligence system to deal with reasoning under similar types of uncertain conditions. 

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Zhou, Chunlai. "Belief Functions on Distributive Lattices." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (2021): 1968–74. http://dx.doi.org/10.1609/aaai.v26i1.8393.

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The Dempster-Shafer theory of belief functions is an important approach to deal with uncertainty in AI.In the theory, belief functions are defined on Boolean algebras of events. In many applications of belief functions in real world problems, however, the objects that we manipulateis no more a Boolean algebra but a distributive lattice. In this paper, we extend the Dempster-Shafer theory to the setting of distributive lattices, which has a mathematical theory as attractive as in that of Boolean algebras.Moreover, we apply this more general theory to a simple epistemic logic the first-degree-en

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Dutta, Palash. "Dempster Shafer Structure-Fuzzy Number Based Uncertainty Modeling in Human Health Risk Assessment." International Journal of Fuzzy System Applications 5, no. 2 (2016): 96–117. http://dx.doi.org/10.4018/ijfsa.2016040107.

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In risk assessment, generally model parameters are affected by uncertainty arises due to vagueness, imprecision, lack of data, small sample sizes etc. Fuzzy set theory and Dempster-Shafer theory (In short DST) of evidence should be explored to handle this type of uncertainty. Representation of parameters of risk assessment models may be Dempster-Shafer structure (in short DSS) and fuzzy numbers. To deal with such situations, it is important to device new techniques. This paper presents two algorithms to combine Dempster-Shafer structure with generalized/normal fuzzy focal elements, generalized

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Xiao, Fuyuan, Junhao Wen, Witold Pedrycz, and Masayoshi Aritsugi. "Complex Evidence Theory for Multisource Data Fusion." Chinese Journal of Information Fusion 1, no. 2 (2024): 134–59. http://dx.doi.org/10.62762/cjif.2024.999646.

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Data fusion is a prevalent technique for assembling imperfect raw data coming from multiple sources to capture reliable and accurate information. Dempster–Shafer evidence theory is one of useful methodologies in the fusion of uncertain multisource information. The existing literature lacks a thorough and comprehensive review of the recent advances of Dempster– Shafer evidence theory for data fusion. Therefore, the state of the art has to be surveyed to gain insight into how Dempster–Shafer evidence theory is beneficial for data fusion and how it evolved over time. In this paper, we first provi

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Butler, A. C., F. Sadeghi, S. S. Rao, and S. R. LeClair. "Computer-aided design/engineering of bearing systems using the Dempster-Shafer theory." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 9, no. 1 (1995): 1–11. http://dx.doi.org/10.1017/s0890060400002043.

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AbstractResearch in computer-aided design/engineering (CAD/E) has focused on enhancing the capability of computer systems in a design environment, and this work has continued in this trend by illustrating the use of the Dempster-Shafer theory to expand the computer’s role in a CAD/E environment. An expert system was created using Dempster-Shafer methods that effectively modeled the professional judgment of a skilled tribologist in the selection of rolling element bearings. A qualitative and symbolic approach was used, but access to simple quantitative models was provided to the expert system s

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