Research on discrepancy discrimination and auxiliary decision making of electric power standard terms

Qian Zheng; Yibo Yong; Qiang Yang; Tianqi Zhong; Tao Zhang; Wangning Guan; Aoao Li

doi:10.1117/12.2679343

16 June 2023 Research on discrepancy discrimination and auxiliary decision making of electric power standard terms

Qian Zheng, Yibo Yong, Qiang Yang, Tianqi Zhong, Tao Zhang, Wangning Guan, Aoao Li

Proceedings Volume 12702, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023); 127021J (2023) https://doi.org/10.1117/12.2679343
Event: International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023), 2023, Changsha, China

Abstract

The standard clauses used in the electric power industry often contain inconsistencies, making it difficult for professionals to select appropriate terms in their work. In this paper, we propose a discrepancy discrimination model based on knowledge graph and natural language processing, using standard clauses of power equipment as the dataset. Furthermore, we construct an ensemble learning model to assist decision-making in the electric power field. The experimental results show that the proposed method is effective in terms of precision and recall. The discrepancy discrimination model has a precision rate of 76.45% and recall rate of 84.72%, while the auxiliary decision-making model has a precision rate of 75.3%. The method is able to effectively identify inconsistencies in equipment standards and provide decision-making advice, providing a valuable reference for standardizing the content of standard terms in the industry.

Citation Download Citation

Qian Zheng, Yibo Yong, Qiang Yang, Tianqi Zhong, Tao Zhang, Wangning Guan, and Aoao Li "Research on discrepancy discrimination and auxiliary decision making of electric power standard terms", Proc. SPIE 12702, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023), 127021J (16 June 2023); https://doi.org/10.1117/12.2679343

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