{"title":"SIMFAC-A New Forecasting Method for Sporadic Time Series","authors":"K. Spicher, Boxing Li, D. Fang","doi":"10.2991/ICMEIT-19.2019.48","DOIUrl":null,"url":null,"abstract":"This essay relates mainly to sporadic FC (forecasting) methods and error measures. The existing related FC methods of sporadic time series (STS), including the SES (Simple Exponential Smoothing), Croston’ s / SBA method and patented WSS method as well as two applicable error metrics APE and THEIL'S U are introduced briefly. Then the focus is laid on the analysis and presentation of a new forecasting yet unpublished method, SIMFAC (1), which is dedicated to STS and includes a new error metric, MEM (Matching Event Metric). For a more comprehensive comparison among methods, Cosine Similarity (CS) metric, will be introduced and applied in this essay.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/ICMEIT-19.2019.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This essay relates mainly to sporadic FC (forecasting) methods and error measures. The existing related FC methods of sporadic time series (STS), including the SES (Simple Exponential Smoothing), Croston’ s / SBA method and patented WSS method as well as two applicable error metrics APE and THEIL'S U are introduced briefly. Then the focus is laid on the analysis and presentation of a new forecasting yet unpublished method, SIMFAC (1), which is dedicated to STS and includes a new error metric, MEM (Matching Event Metric). For a more comprehensive comparison among methods, Cosine Similarity (CS) metric, will be introduced and applied in this essay.
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