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Issue title: Fuzzy Logic based Decision Making
Guest editors: Erik Maehle, Norbert Stoll and Chao-Hsien Chu
Article type: Research Article
Authors: Shang, Ying* | Kang, Liyan | Liu, Xinran | Sun, Lina | Li, Zhongcheng | Zhang, Muxin | Wu, Qiutong
Affiliations: Electric Power Research Institute of State Grid Power Co., Ltd, Shenyang, Liaoning 110006, China
Correspondence: [*] Corresponding author: Ying Shang, Electric Power Research Institute of State Grid Power Co., Ltd, Shenyang, Liaoning 110006, China. E-mail: highlightme@126.com.
Abstract: In order to construct the closed-loop management system of abnormal early warning, the decision tree algorithm, survival analysis algorithm and logistic regression algorithm are used synthetically. The improved logistic regression algorithm proposed in this study is used to establish the abnormal early warning model, identify the abnormal tendency in advance, and construct the active monitoring and closed-loop operation and maintenance management system to provide the key technical support. The results show that this method improves the real-time processing of data acquisition, reduces the impact on data acquisition, improves the efficiency of operation and maintenance, and carries out timely and accurate early warning. This method proposes active monitoring mechanism based on complex event processing and fast fault location technology based on expert database. From this point of view, testing the key technical indicators of the system proves that the system can effectively promote the improvement of business operation and maintenance efficiency, quality and management level.
Keywords: Alteration early warning, closed-loop management system, operation and maintenance management, information collection
DOI: 10.3233/JCM-191011
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 19, no. S1, pp. 69-75, 2019
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