Compound Credibility for Conflicting Evidence Combination: An Autoencoder-<i>K</i>-Means Approach

Shang, Qiuyan; Li, Hanwen; Deng, Yong; Cheong, Kang Hao

doi:10.1109/tsmc.2021.3130187

Cited by 31 publications

(6 citation statements)

References 43 publications

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“…In order to solve this problem, many relevant theories have been proposed, such as Z-number [2], intuitionistic fuzzy set [3], [4], rough set [5], [6], random permutation set [7], Dempster-Shafer evidence theory (DSET), etc [8]- [10]. Owing to its advantages in probability distribution of uncertain information, DSET and its branches [11] are widely used in many fields, such as decision-making [12]- [17], pattern recognition [18], [19], multi-source information fusion [20]- [22], classification decision [23], [24], reasoning [25]- [27], fault diagnosis [28], etc [29]- [34].…”

Section: Introductionmentioning

confidence: 99%

A novel quantum belief entropy for uncertainty measure in complex evidence theory

Wu,

Xiao

2024

Information Sciences

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Section: Introductionmentioning

confidence: 99%

A novel quantum belief entropy for uncertainty measure in complex evidence theory

Wu,

Xiao

2024

Information Sciences

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“…This feeling of safety enables students to test new ideas, question assumptions, and explore complex subjects in ways that increase their contact with content and make them more motivated to learn from within. Moreover, successful task conflict handling encourages critical thought and problem-solving abilities that are essential for scholastic achievement and personal development (Shang, Li, Deng & Cheong, 2021). When pupils encounter divergent perspectives or difficulties in small group activities/cooperative undertakings, they encounter situations that require them to analyze, assess & integrate information from distinct perspectives (Adams & Plaatjies, 2021).…”

Section: Introductionmentioning

confidence: 99%

Enhancing Student Motivation at College Level Through Effective Conflict Management Strategies

Siddique,

Ali,

Basit

2024

JSRD

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This study investigated the impact of conflict management strategies (task, relationship, and value) on college students' motivation toward learning. A sample of 392 students from the intermediate classes in public and private colleges from urban & rural areas participated. Data were collected using a self-developed rating scale and analyzed with SPSS software. The results revealed that task conflict management showed little variations between school types, relation & value conflict management significantly affected motivation, with public schools outperforming private ones. Gender-based differences were noted in the relationship conflict management, with male respondents displaying lower motivation levels. Urban schools generally exhibited lower motivation than rural schools across all conflict resolution categories. Present results emphasized how crucial it is to use prevention approaches towards specific conflicts and to apply positive stimulation to students to promote more positive relations and thus motivate students in different educational environments. If the technologies employed where novelties’ little chance of support would be available to those lacking in IT expertise.

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“…The data fusion technology may prove to be more helpful to meet the security risk management needs of the tunnel construction than point-based methods 11 . Over the years, various information fusion studies have been proposed, such as Dempster–Shafer (D–S) evidence theory 12 , 13 , maximum entropy method 14 , rough sets 15 , etc. Among the above information fusion methods, D–S evidence theory is an effective and commonly used method in the field of information fusion.…”

Section: Introductionmentioning

confidence: 99%

A multi-source information fusion approach in tunnel collapse risk analysis based on improved Dempster–Shafer evidence theory

Qiu

Huang

et al. 2022

Sci Rep

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The tunneling collapse is the main engineering hazard in the construction of the drilling-and-blasting method. The accurate assessment of the tunneling collapse risk has become a key issue in tunnel construction. As for assessing the tunneling collapse risk and providing basic risk controlling strategies, this research proposes a novel multi-source information fusion approach that combines Bayesian network (BN), cloud model (CM), support vector machine (SVM), Dempster–Shafer (D–S) evidence theory, and Monte Carlo (MC) simulation technique. Those methods (CM, BN, SVM) are used to analyze multi-source information (i.e. statistical data, physical sensors, and expert judgment provided by humans) respectively and construct basic probability assignments (BPAs) of input factors under different risk states. Then, these BPAs will be merged at the decision level to achieve an overall risk evaluation, using an improved D–S evidence theory. The MC technology is proposed to simulate the uncertainty and randomness of data. The novel approach has been successfully applied in the case of the Jinzhupa tunnel of the Pu-Yan Highway (Fujian, China). The results indicate that the developed new multi-source information fusion method is feasible for (a) Fusing multi-source information effectively from different models with a high-risk assessment accuracy of 98.1%; (b) Performing strong robustness to bias, which can achieve acceptable risk assessment accuracy even under a 20% bias; and (c) Exhibiting a more outstanding risk assessment performance (97.9% accuracy) than the single-information model (78.8% accuracy) under a high bias (20%). Since the proposed reliable risk analysis method can efficiently integrate multi-source information with conflicts, uncertainties, and bias, it provides an in-depth analysis of the tunnel collapse and the most critical risk factors, and then appropriate remedial measures can be taken at an early stage.

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Compound Credibility for Conflicting Evidence Combination: An Autoencoder-K-Means Approach

Cited by 31 publications

References 43 publications

A novel quantum belief entropy for uncertainty measure in complex evidence theory

A novel quantum belief entropy for uncertainty measure in complex evidence theory

Enhancing Student Motivation at College Level Through Effective Conflict Management Strategies

A multi-source information fusion approach in tunnel collapse risk analysis based on improved Dempster–Shafer evidence theory

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