Automated Classification and Grading of Power System Database Fields Based on Rule Association and Probabilistic Reasoning.

Recent advancements in power system databases have led to a significant increase in the amount of data field entries, which in turn requires efficient classification and grading methods. This paper proposes an automated approach to classify and grade power system database fields using rule association and probabilistic reasoning. The purpose of this study is to develop a reliable method to accurately classify and grade the various fields in power system databases. The research methodology involves creating a set of rules based on association analysis and using probabilistic reasoning to determine the field grades. The results demonstrate that the proposed approach achieves high classification accuracy and grading consistency. The study concludes that the automated method can effectively classify and grade power system database fields, thereby facilitating efficient data analysis and decision-making processes.