{"title":"基于灰色线性回归模型的船用电缆剩余寿命预测研究","authors":"Yi Wei, Yancheng Liu, Yulong Ji, Chuan Wang","doi":"10.1109/LEITS.2010.5664937","DOIUrl":null,"url":null,"abstract":"Predicting residual life of cable plays a key role in ship management. In this paper, the Grey Linear Regression Model is used for residual life prediction of shipboard cable under influence of multi-factors. The method is proved effectively by the comparison beween the actual aging data and the data acquired by the traditional Arrhenius Equation.","PeriodicalId":173716,"journal":{"name":"2010 International Conference on Logistics Engineering and Intelligent Transportation Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Study on Residual Life Prediction of Shipboard Cable Based on Grey Linear Regression Model\",\"authors\":\"Yi Wei, Yancheng Liu, Yulong Ji, Chuan Wang\",\"doi\":\"10.1109/LEITS.2010.5664937\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Predicting residual life of cable plays a key role in ship management. In this paper, the Grey Linear Regression Model is used for residual life prediction of shipboard cable under influence of multi-factors. The method is proved effectively by the comparison beween the actual aging data and the data acquired by the traditional Arrhenius Equation.\",\"PeriodicalId\":173716,\"journal\":{\"name\":\"2010 International Conference on Logistics Engineering and Intelligent Transportation Systems\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Logistics Engineering and Intelligent Transportation Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LEITS.2010.5664937\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Logistics Engineering and Intelligent Transportation Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LEITS.2010.5664937","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study on Residual Life Prediction of Shipboard Cable Based on Grey Linear Regression Model
Predicting residual life of cable plays a key role in ship management. In this paper, the Grey Linear Regression Model is used for residual life prediction of shipboard cable under influence of multi-factors. The method is proved effectively by the comparison beween the actual aging data and the data acquired by the traditional Arrhenius Equation.