Learning Emotion Assessment Method Based on Belief Rule Base and Evidential Reasoning

Chen, Haobing; Zhou, Guohui; Zhang, Xin; Zhu, Hailong; He, Wei

doi:10.3390/math11051152

Cited by 4 publications

(2 citation statements)

References 23 publications

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“…In this paper, a projection covariance matrix adaptive evolution strategy (P-CMA-ES) is used to implement the optimization of the model. The purpose of the optimization process is to improve the performance of BRB by finding the optimal model parameters [31,32]. The optimization process of the algorithm is shown in Figure 1.…”

Section: Optimization Methods Of the Model Parametersmentioning

confidence: 99%

A New Fault Diagnosis Method Based on Belief Rule Base With Attribute Reliability Considering Multi-Fault Features

Li,

Yin,

et al. 2023

IEEE Access

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Fault diagnosis plays a critical role in system health management. However, practical fault diagnosis encounters several challenges such as limited observational information, system complexity, and environmental disturbances. Belief rule base with attribute reliability (BRB-r) provides a valuable solution to these problems. In BRB-r, the reliability of the input information directly affects the reliability of the observed metrics and subsequently the accuracy of the output belief degree. To strike a balance between the reliability and accuracy of fault diagnosis models, a new fault diagnosis method for BRB-r considering multi-fault features (BRB-mr) is introduced. In the BRB-mr model, the reliability calculation method for attributes considering multi-fault features is proposed. The obtained attribute reliability is then introduced into the calculation of the matching degree, which ultimately reduces the interference of unreliable information to obtain more accurate and reliable diagnostic results. In addition, an optimization model is used to mitigate the effect of uncertainty in expert knowledge. The effectiveness of the method is validated by a case study of diesel engine fault diagnosis.INDEX TERMS Fault diagnosis, belief rule base, attribute reliability, multi-fault features.

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Section: Optimization Methods Of the Model Parametersmentioning

confidence: 99%

A New Fault Diagnosis Method Based on Belief Rule Base With Attribute Reliability Considering Multi-Fault Features

Li,

Yin,

et al. 2023

IEEE Access

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“…These belief distributions are used as evidence and fused using the ER algorithm. The obtained results are used as inputs to the PBRB to reduce the number of attributes [27]. Then, the PBRB model is constructed, and inference is performed to obtain the evaluation results.…”

Section: Problem Formulation Of Education Quality Evaluationmentioning

confidence: 99%

A new method for education quality evaluation based on belief rule base with power set and evidential reasoning

Liang,

Zhou,

et al. 2023

Preprint

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The evaluation of education quality is an important part of the construction of the education system, and it is a direct path to improving education quality. Education quality is a complex evaluation system that takes into account a number of dimensions, such as objectives, attitudes and outcomes. In teaching practice, these dimensions are often good or bad, making it difficult to assess the results of a comprehensive evaluation, leading to the problem of ignorance. Therefore, a belief rule base with power set (PBRB) is used to construct the model for education quality evaluation. The model extends the set of evaluation results into a power set that expresses a variety of evaluation ratings that are difficult to characterize, and uses the BRB to assign belief degrees to each rating in the power set. In addition, because the evaluation of education quality requires a great number of indicators, the BRB faces the rule combination explosion problem. To solve the problem, the transformation matrix is constructed to unify the evaluation indicators, which are then fused using the evidential reasoning (ER) algorithm to reduce the number of PBRB attributes. Finally, the parameters are optimized with the projected covariance matrix adaptive evolution strategy (P-CMA-ES) to improve the model accuracy. According to the experimental results, compared with other methods, the education quality evaluation method based on the EPBRB proposed in this paper can give a clear evaluation grade and has better accuracy and stability.

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An Explainable Student Performance Prediction Method Based on Dual-Level Progressive Classification Belief Rule Base

Mai,

Wei,

et al. 2024

Electronics

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Explainable artificial intelligence (XAI) is crucial in education for making educational technologies more transparent and trustworthy. In the domain of student performance prediction, both the results and the processes need to be recognized by experts, making the requirement for explainability very high. The belief rule base (BRB) is a hybrid-driven method for modeling complex systems that integrates expert knowledge with transparent reasoning processes, thus providing good explainability. However, class imbalances in student grades often lead models to ignore minority samples, resulting in inaccurate assessments. Additionally, BRB models face the challenge of losing explainability during the optimization process. Therefore, an explainable student performance prediction method based on dual-level progressive classification BRB (DLBRB-i) has been proposed. Principal component regression (PCR) is used to select key features, and models are constructed based on selected metrics. The BRB’s first layer classifies data broadly, while the second layer refines these classifications for accuracy. By incorporating explainability constraints into the population-based covariance matrix adaptation evolution strategy (P-CMA-ES) optimization process, the explainability of the model is ensured effectively. Finally, empirical analysis using real datasets validates the diagnostic accuracy and explainability of the DLBRB-i model.

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Learning Emotion Assessment Method Based on Belief Rule Base and Evidential Reasoning

Cited by 4 publications

References 23 publications

A New Fault Diagnosis Method Based on Belief Rule Base With Attribute Reliability Considering Multi-Fault Features

A New Fault Diagnosis Method Based on Belief Rule Base With Attribute Reliability Considering Multi-Fault Features

A new method for education quality evaluation based on belief rule base with power set and evidential reasoning

An Explainable Student Performance Prediction Method Based on Dual-Level Progressive Classification Belief Rule Base

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