{"title":"基于FP-growth算法的设备维护数据挖掘","authors":"Juan Gu, Tianyuan Jiang, Lei Shen","doi":"10.1117/12.2682590","DOIUrl":null,"url":null,"abstract":"This paper extracts the maintenance records of the equipment in the equipment big data platform, uses the FP-growth algorithm to mine association rules, obtains typical association rules, and mines the associations of various faults occurring in regions, motorcycle hours, etc., to provide decision support for maintenance plan formulation, maintenance equipment procurement and storage, and to provide technical support for improving the effectiveness of equipment support.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"08 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Equipment maintenance data mining based on FP-growth algorithm\",\"authors\":\"Juan Gu, Tianyuan Jiang, Lei Shen\",\"doi\":\"10.1117/12.2682590\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper extracts the maintenance records of the equipment in the equipment big data platform, uses the FP-growth algorithm to mine association rules, obtains typical association rules, and mines the associations of various faults occurring in regions, motorcycle hours, etc., to provide decision support for maintenance plan formulation, maintenance equipment procurement and storage, and to provide technical support for improving the effectiveness of equipment support.\",\"PeriodicalId\":177416,\"journal\":{\"name\":\"Conference on Electronic Information Engineering and Data Processing\",\"volume\":\"08 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference on Electronic Information Engineering and Data Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2682590\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference on Electronic Information Engineering and Data Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2682590","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Equipment maintenance data mining based on FP-growth algorithm
This paper extracts the maintenance records of the equipment in the equipment big data platform, uses the FP-growth algorithm to mine association rules, obtains typical association rules, and mines the associations of various faults occurring in regions, motorcycle hours, etc., to provide decision support for maintenance plan formulation, maintenance equipment procurement and storage, and to provide technical support for improving the effectiveness of equipment support.