The evaluation method of college teachers’ morality considering intelligent emotion recognition and data mining algorithm

Hu, Xingcui

doi:10.1080/08839514.2023.2186413

Cited by 2 publications

(1 citation statement)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Overall, the method is accurate in terms of prediction and generalization, as discussed in detail in the research findings. Initially, scientists used statistical learning to assess risk (Hu, 2023). Credit risk analysis paved the way for techniques like regression.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Artificial Intelligence Data Mining Algorithm in Enterprise Management Risk Assessment

Zhu

2024

International Journal of Information Systems and Supply Chain Management

View full text Add to dashboard Cite

For governmental and non-governmental enterprises to tackle risk management with conviction, enterprise management risk assessment (EMRA) is required. This work proposes a research methodology based on an AI-based data mining algorithm (MSVM+EFCNN) for evaluating enterprise-related risks. Initially, all the possible risk assessment indexes of the enterprise are established using a large variety of identification parameters. Then, the data mining algorithms are trained by considering the previous data for building an EMRA model. At last, the current conditions are analyzed using a cluster of risk indicators, and the risk index is identified via the EMRA model. The support vector machine is used for classification purposes, and the fuzzy-based convolutional neural network is enhanced with a genetic algorithm for creating the enterprise risk assessment. The results obtained after keen analysis and experimentation indicate that the data mining algorithms used in this work can evaluate the enterprise-related risks effectively.

show abstract

Section: Literature Reviewmentioning

confidence: 99%