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Journal articles on the topic 'Evidence combination'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Yin Liu, Yin Liu, and Yang Zhang Yin Liu. "A Weighted Evidence Combination Method for Multisensor Data Fusion." 網際網路技術學刊 23, no. 3 (2022): 553–60. http://dx.doi.org/10.53106/160792642022052303013.

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<p>Multisensor information fusion exerts a key part in lots of practical usages. Dempster-shafer evidence theory has drawn extensive attention in many scopes of information fusion due to its flexibility and effectiveness in dealing with uncertain data without aforehand data. But when combining highly contradictory evidence with Dempster’s combinatorial principles, it can result in counterintuitive results. To solve the issue, the study proposes a multi-sensor data weighted evidence combination fusion method based on inter-evidence difference measure. Firstly, different measures including

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2

Shafer, Glenn. "The combination of evidence." International Journal of Intelligent Systems 1, no. 3 (1986): 155–79. http://dx.doi.org/10.1002/int.4550010302.

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Wu, Shang, and Guo Chu Chen. "Combination of Conflicting Evidence Based on Relative Entropy." Applied Mechanics and Materials 724 (January 2015): 318–22. http://dx.doi.org/10.4028/www.scientific.net/amm.724.318.

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Combination of conflicting evidence usually resulted in illogical outcome. In order to solve this problem, an approach to acquire evidence reliability based on relative entropy was proposed by researching the evidence theory and relative entropy. Firstly, the weights of evidences were calculated by evidence distance, reference evidence was obtained by weighting and meaning. Then relative reliabilities were achieved by calculating the relative entropy between original evidence and reference evidence. In the end, final outcome was achieved by D-S composition. This method can commendably extract

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4

Lee, Joon Ho. "Analyses of multiple evidence combination." ACM SIGIR Forum 31, SI (1997): 267–76. http://dx.doi.org/10.1145/278459.258587.

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5

Lesmo, Leonardo, Lorenza Saitta, and Pietro Torasso. "Evidence combination in expert systems." International Journal of Man-Machine Studies 22, no. 3 (1985): 307–26. http://dx.doi.org/10.1016/s0020-7373(85)80006-7.

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6

Liu, Jian. "Weighted Combination Method of Conflict Evidence Based on Deviation." Advanced Materials Research 457-458 (January 2012): 1581–85. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.1581.

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To solve the problem that D-S evidence combination method may lose effectiveness when evidences are highly or full conflict, we propose weighted combination method of conflict evidence based on deviation. We think, different evidence source is under different circumstance, so the importance of each evidence is different. It is necessary to give weight to every evidence, then conflict probability can only just be assigned. Deviation is a good standard to measure errors. In the circumstance the difference between probabilities from certain evidence source and their mean is too large, that indica

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7

Kalhan, Atul, and Alan Rees. "Statin/ezetimibe combination therapy: emerging evidence." Current Opinion in Lipidology 22, no. 2 (2011): 146–47. http://dx.doi.org/10.1097/mol.0b013e3283447835.

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8

Florea, Mihai Cristian, Anne-Laure Jousselme, Éloi Bossé, and Dominic Grenier. "Robust combination rules for evidence theory." Information Fusion 10, no. 2 (2009): 183–97. http://dx.doi.org/10.1016/j.inffus.2008.08.007.

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9

Liu, Weiru, and Jun Hong. "Reinvestigating Dempster's Idea on Evidence Combination." Knowledge and Information Systems 2, no. 2 (2000): 223–41. http://dx.doi.org/10.1007/s101150050012.

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10

Yang, Jian-Bo, and Dong-Ling Xu. "Evidential reasoning rule for evidence combination." Artificial Intelligence 205 (December 2013): 1–29. http://dx.doi.org/10.1016/j.artint.2013.09.003.

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11

Chin, Kuo-Hsuan, and Chi Ho Lau. "Inflation Forecast Combination: Evidence from Taiwan." Review of Economics 75, no. 3 (2024): 215–31. https://doi.org/10.1515/roe-2024-0054.

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Abstract We study the benefit of considering the forecast combination over the individual forecasts generated from the single models in predicting the inflation. In particular, we contribute to the current studies since we rarely find, to the best of our knowledge, the published papers that study the performance of the forecast combination in predicting Taiwan’s inflation, at least from both the Bayesian and the forecast stability perspectives. The models that we adopt to generate the individual forecasts include the random-walk (RW) model, Phillips curve-based (PC) model, the vector autoregre

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12

Tang, Qi, Jianyu Xiao, and Kefeng Wu. "A novel evidence combination method based on stochastic approach for link-structure analysis algorithm and Lance-Williams distance." PeerJ Computer Science 9 (April 18, 2023): e1307. http://dx.doi.org/10.7717/peerj-cs.1307.

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In response to the traditional Dempster–Shafer (D-S) combination rule that cannot handle highly conflicting evidence, an evidence combination method based on the stochastic approach for link-structure analysis (SALSA) algorithm combined with Lance-Williams distance is proposed. Firstly, the degree of conflict between evidences is calculated based on the number of correlation coefficients between evidences. Then, the evidences with a number of correlation coefficients greater than the average number of correlation coefficients of evidence are connected to construct an evidence association netwo

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13

Han, Deqiang, Yong Deng, and Chongzhao Han. "Sequential weighted combination for unreliable evidence based on evidence variance." Decision Support Systems 56 (December 2013): 387–93. http://dx.doi.org/10.1016/j.dss.2013.05.004.

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14

Yao, Jie, Tao Hu, and Jian Jun Yang. "Information Processing with Combination Method for Dependent Evidences Based on Principal Component Analysis." Advanced Materials Research 1022 (August 2014): 304–10. http://dx.doi.org/10.4028/www.scientific.net/amr.1022.304.

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To meet the requirement that evidences must be independent for evidences combination in D-S evidence theory when the information processing, the dependence among evidences should be eliminated, so a new combination method of dependent evidences based on the Principal Component Analysis (PCA) is presented. The high-dimensional dependent evidences are replaced by the new low-dimensional independent evidences to reduce the dimensions following the guiding rule of PCA, and then the probability under the new evidences is calculated. The new independent evidences are combined with the combination ru

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15

Su, Xiaoyan, Shuwen Shang, Leihui Xiong, Ziying Hong, and Jian Zhong. "Research on dependent evidence combination based on principal component analysis." Mathematical Biosciences and Engineering 21, no. 4 (2024): 4853–73. http://dx.doi.org/10.3934/mbe.2024214.

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<abstract><p>Dempster-Shafer evidence theory, as a generalization of probability theory, is a powerful tool for dealing with a variety of uncertainties, such as incompleteness, ambiguity, and conflict. Because of its advantages in information fusion compared with traditional probability theory, it is widely used in various fields. However, the classic Dempster's combination rule assumes that evidences are independent of each other, which is difficult to satisfy in real life. Ignoring the dependence among the evidences will lead to unreasonable fusion results, and even wrong conclus

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16

Shalev, Ron. "The Information Content of Business Combination Disclosure Level." Accounting Review 84, no. 1 (2009): 239–70. http://dx.doi.org/10.2308/accr.2009.84.1.239.

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ABSTRACT: This study explores causes and effects of business combinations disclosure level. Investigating the association between disclosure level on business combination and acquirers' future performance, I find that acquirers' future performance as measured by the change in ROA and by abnormal stock returns increases with abnormal levels of disclosure on business combinations. Investigating the determinants of business combination disclosure, I find that the disclosure level on business combinations decreases with abnormal levels of the purchase price allocated to goodwill. Both results prov

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17

Miller, Alexander L. "Combination Treatments for Schizophrenia." CNS Spectrums 9, S9 (2004): 19–23. http://dx.doi.org/10.1017/s1092852900004363.

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ABSTRACTCombination treatments, especially combinations of antipsychotics, are used frequently for schizophrenia, despite a paucity of evidence regarding their safety and efficacy. Because the literature basis is weak and expert recommendations are largely lacking, providers should be vigilant in documenting improved outcomes for patients thought to benefit from combination treatments. Target symptoms that have been studied include psychosis, cognitive deficits, and negative symptoms. The strongest evidence is for augmentation of clozapine with another antipsychotic or with electroconvulsive t

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18

Zhu, Jing, Cheng Jun Zhang, Li Fang Hu, and Yi Cheng Zheng. "A New Fast Combination Method of Conflict Evidences Based on Model Modification." Advanced Materials Research 694-697 (May 2013): 2835–41. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.2835.

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In the belief function theory, the combination of highly conflicting evidences is a research focus,and the key lies in both the rationality and timeliness of combination method.This paper analyzes deeply the existing strategy of model modification, and putsforward a new rapid evidence synthesis method based on model modification. The average evidence ofweighted combination on mean evidence isfirstly given, then fast combination on pignistic transformation can be realized. Thus the BBM accordancewith the principle of proportion redistribution isgot. This method has the advantage of Murphy’s met

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19

HAN, De-Qiang, Yong DENG, Chong-Zhao HAN, and Zhi-Qiang HOU. "Weighted evidence combination based on distance of evidence and uncertainty measure." JOURNAL OF INFRARED AND MILLIMETER WAVES 30, no. 5 (2012): 396–400. http://dx.doi.org/10.3724/sp.j.1010.2011.00396.

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20

Wang, Jianwei, Fuyuan Xiao, Xinyang Deng, Liguo Fei, and Yong Deng. "Weighted Evidence Combination Based on Distance of Evidence and Entropy Function." International Journal of Distributed Sensor Networks 12, no. 7 (2016): 3218784. http://dx.doi.org/10.1177/155014773218784.

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21

XIA, Wen-jun, Lin-hu ZHU, and Tao-rong LU. "Evidence combination approach based on uncertainty measure." Journal of Computer Applications 29, no. 8 (2009): 2257–59. http://dx.doi.org/10.3724/sp.j.1087.2009.02257.

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22

Wallace, Mark S., Richard L. Rauck, and Timothy Deer. "Ziconotide Combination Intrathecal Therapy: Rationale and Evidence." Clinical Journal of Pain 26, no. 7 (2010): 635–44. http://dx.doi.org/10.1097/ajp.0b013e3181e017df.

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23

Han, Deqiang, Yong Deng, Chongzhao Han, and Yi Yang. "A Novel Batch-Mode Evidence Combination Approach." Sensor Letters 9, no. 5 (2011): 2073–77. http://dx.doi.org/10.1166/sl.2011.1521.

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24

Zhang, W., A. Collins, and N. E. Morton. "Combination of Linkage Evidence in Complex Inheritance." Human Heredity 52, no. 3 (2001): 132–35. http://dx.doi.org/10.1159/000053367.

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25

Awad, Mamoun, Latifur Khan, and Bhavani Thuraisingham. "Predicting WWW surfing using multiple evidence combination." VLDB Journal 17, no. 3 (2006): 401–17. http://dx.doi.org/10.1007/s00778-006-0014-1.

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26

Song, Yafei, Xiaodan Wang, Lei Lei, and Yaqiong Xing. "Credibility decay model in temporal evidence combination." Information Processing Letters 115, no. 2 (2015): 248–52. http://dx.doi.org/10.1016/j.ipl.2014.09.022.

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27

Torra, Vicenç. "A new combination function in evidence theory." International Journal of Intelligent Systems 10, no. 12 (1995): 1021–33. http://dx.doi.org/10.1002/int.4550101202.

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28

Zhu, Jing, Chen Xi Wang, Li Fang Hu, and Yi Cheng Zheng. "New Methods of Evidence Conflict Measurement Based on Conjunctive Combination Rule." Applied Mechanics and Materials 256-259 (December 2012): 2877–85. http://dx.doi.org/10.4028/www.scientific.net/amm.256-259.2877.

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In the effective combination of conflicting evidences using the Dempster-Shafer evidence theory, the first step is to reasonably measure the conflict between evidences, but there are limitations in the existing conflict measurement methods. Two new conflict measurement methods based on conjunctive combination rule are put forword, which overcome the limitations of the existing measurement methods. They have four satisfactory properties. Firstly, new methods can measure the total conflict between any pieces of evidence simultaneously, which can satisfy the interchangeability and combinability.

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29

Palaniyappan, Lena, Lisa Insole, and Nicol Ferrier. "Combining antidepressants: a review of evidence." Advances in Psychiatric Treatment 15, no. 2 (2009): 90–99. http://dx.doi.org/10.1192/apt.bp.107.004820.

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SummarySequenced (stepped) treatment approaches are widely endorsed in the management of depression. Combining antidepressants is a recognised step for those failing to respond to monotherapy. Despite the limited evidence base, this strategy is widely used by clinicians in practice. Not every combination used clinically has a sound neuropharmacological rationale and the use of such combinations may increase the side-effect burden without any additional advantage to the patient. Efficacy of various antidepressant combinations along with the data on side-effect profile and toxicity of such combi

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30

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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31

Alpert, Sofiia. "Comparison of the new improved combination approach that deal with conflict data with Yager’s solution approach." Ukrainian journal of remote sensing, no. 17 (June 27, 2018): 14–17. http://dx.doi.org/10.36023/ujrs.2018.17.125.

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Dempster-Shafer evidence theory is the most effective approach to process imprecise and incomplete information. But Dempster’s combination rule can not deal with conflicting data and can lead to illogical results. That’s why the combination of conflicting bodies of evidence is one of the most difficult problems. Yager’s solution approach can process conflicting data, but correlation among evidences is not taken into account. It was proposed a new combination method, that uses correlation among different bodies of evidence and give accurate results.

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32

Pan, Guang, and Lin Li Wu. "Information Fusion Based on Improved D-S Evidence Theory." Applied Mechanics and Materials 411-414 (September 2013): 49–52. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.49.

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Dempster-Shafer evidence theory is an efficient method to process uncertain, incomplete and vague information in data fusion. Aiming at the failure of conditional D-S evidence theory in dealing with conflicting evidences, an improved D-S combination rule is recommended. The proposed method utilizes the information quantity of evidence and assigns the conflict factor to every focus element based on average support degree. The simulations show that the proposed D-S combination rule can effectively solve thorny problems for conflicting evidences.

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33

Zhao, Zhuan Zhe, Min Ping Jia, Kang He, Hao Zhou, and Yu Jie Ding. "Approach of Combination of Weighted Evidence Based on Evidential Closeness Degree and its Application." Advanced Materials Research 630 (December 2012): 377–82. http://dx.doi.org/10.4028/www.scientific.net/amr.630.377.

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Since the information fusion based on Dempster-Shafer(D-S) evidence theory involves counter-intuitive behaviors when evidences highly conflict, a new approach of combination of weighted based on evidence closeness degree is proposed and applied in fault diagnosis．Firstly, the calculation method of evidence distance and evidential closeness degree as well as its revision are given according to the relevance and importance of various evidence sources; Then the closeness degree is normalized in order to obtain the weights of evidence sources. And the information fusion is realized with the base o

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34

Gawey, Lauren, Nazanin Saedi, and Amelia Hausauer. "Neurotoxins and Combination Therapies." Dermatologic Surgery 50, no. 9S (2024): S85—S90. http://dx.doi.org/10.1097/dss.0000000000004359.

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BACKGROUND Facial aging involves multilevel changes, extending from the skin to deep support structures. A comprehensive treatment approach targeting the many aspects of facial dynamics and architecture is often necessary to achieve optimal correction, prevent changes before they occur, and/or help highlight inherited features. OBJECTIVE To explore the integration of botulinum toxin type A (BoNT-A) into multimodal aesthetic treatment plans. MATERIALS AND METHODS This article reviews evidence supporting the combination of BoNT-A with other minimally invasive cosmetic therapies, including dermal

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35

Ye, Fang, Jie Chen, and Yuan Tian. "A Robust DS Combination Method Based on Evidence Correction and Conflict Redistribution." Journal of Sensors 2018 (June 5, 2018): 1–12. http://dx.doi.org/10.1155/2018/6526018.

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To eliminate potential evidence conflicts, an effective and accurate DS combination method is addressed in this paper. DS evidence theory is an outstanding information fusion approach with valid uncertainty treatment. Nevertheless, there are some limitations of the usage of the DS evidence theory. On the one hand, due to the complexity of a combat measurement environment and the inconsistency of sensor capabilities, sensor sources have enormous uncertainty, which would inevitably cause conflicts for evidence combination. On the other hand, DS combination rule realizes the unity property of fus

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36

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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37

Kumari, Alka, Niyamat A. Siddiqui, Sweta Kumari, et al. "Combination Therapy for Post-Kala-Azar Dermal Leishmaniasis: A Literature Review of Current Evidence." Indian Journal of Dermatology 69, no. 5 (2024): 396–405. http://dx.doi.org/10.4103/ijd.ijd_612_22.

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Abstract Post-kala-azar dermal leishmaniasis (PKDL) is a neglected skin disease that has tremendous epidemiological significance as a reservoir of Leishmania parasites. Relapse, drug resistance, non-compliance to prolonged treatment, poor health-seeking behaviour, along with limited therapeutic options pose a significant impact on the management of PKDL. In this study, we aimed to review the efficacy, safety and tolerability data of combination therapies for PKDL in the published literature. We have also described patients’ compliance with treatment and associated co-infections in PKDL. A comp

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38

Chen, Jing, Li-Yun Jiang, and Ge-Xia Qiao. "Taxonomic position of Hormaphis similibetulae Qiao & Zhang, 2004 (Hemiptera, Aphididae): molecular and biological evidence." ZooKeys 111 (June 22, 2011): 11–18. https://doi.org/10.3897/zookeys.111.1284.

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The taxonomic position of <i>Hormaphis similibetulae </i>Qiao & Zhang, 2004 has been reexamined. The phylogenetic position of <i>H. similibetulae </i>was inferred by maximum parsimony, maximum likelihood and Bayesian analyses on the basis of partial nuclear elongation factor-1α and mitochondrial tRNA leucine/cytochrome oxidase II sequences. The results showed that this species fell into the clade of <i>Hamamelistes</i> species, occupying a basal position, and was clearly distinct from other <i>Hormaphis</i> species. A closer relationship between <i>H. similibetulae</i> and <i>Hamamelistes<

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39

Yang, Kehua, Tian Tan, and Wei Zhang. "An Evidence Combination Method based on DBSCAN Clustering." Computers, Materials & Continua 57, no. 2 (2018): 269–81. http://dx.doi.org/10.32604/cmc.2018.03696.

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40

Lee, Gyesung. "An Approximate Evidence Combination Scheme for Increased Efficiency." KIPS Transactions:PartB 9B, no. 1 (2002): 17–22. http://dx.doi.org/10.3745/kipstb.2002.9b.1.017.

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41

Xiong, Leihui, Xiaoyan Su, and Hong Qian. "Conflicting evidence combination from the perspective of networks." Information Sciences 580 (November 2021): 408–18. http://dx.doi.org/10.1016/j.ins.2021.08.088.

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42

Bai, Jing. "A New Improved Combination Rule of Evidence Theory." Journal of Information and Computational Science 11, no. 18 (2014): 6489–96. http://dx.doi.org/10.12733/jics20104991.

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43

Xing, Xiaochen, Yuanwen Cai, Zhengyu Zhao, and Long Cheng. "Weighted evidence combination based on improved conflict factor." Journal of Discrete Mathematical Sciences and Cryptography 19, no. 1 (2016): 173–84. http://dx.doi.org/10.1080/09720529.2015.1113666.

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44

Premaratne, Kamal, Duminda A. Dewasurendra, and Peter H. Bauer. "Evidence Combination in an Environment With Heterogeneous Sources." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 37, no. 3 (2007): 298–309. http://dx.doi.org/10.1109/tsmca.2007.893456.

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45

YAGER, RONALD R. "QUASI‐ASSOCIATIVE OPERATIONS IN THE COMBINATION OF EVIDENCE." Kybernetes 16, no. 1 (1987): 37–41. http://dx.doi.org/10.1108/eb005755.

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46

Halperin, Daniel T. "Combination HIV prevention must be based on evidence." Lancet 373, no. 9663 (2009): 544–45. http://dx.doi.org/10.1016/s0140-6736(09)60200-2.

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47

Ng, Geok See, and Harcharan Singh. "Data equalisation with evidence combination for pattern recognition." Pattern Recognition Letters 19, no. 3-4 (1998): 227–35. http://dx.doi.org/10.1016/s0167-8655(98)00005-1.

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48

Yamada, Koichi. "A new combination of evidence based on compromise." Fuzzy Sets and Systems 159, no. 13 (2008): 1689–708. http://dx.doi.org/10.1016/j.fss.2007.11.019.

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49

Yoshida, Kazuhiro, Kazuya Yamaguchi, Shinji Osada, et al. "Challenge for a better combination with basic evidence." International Journal of Clinical Oncology 13, no. 3 (2008): 212–19. http://dx.doi.org/10.1007/s10147-008-0793-z.

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50

Deng, Xinyang, Deqiang Han, Jean Dezert, Yong Deng, and Yu Shyr. "Evidence Combination From an Evolutionary Game Theory Perspective." IEEE Transactions on Cybernetics 46, no. 9 (2016): 2070–82. http://dx.doi.org/10.1109/tcyb.2015.2462352.

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