{"title":"基于云的统计分布识别模块","authors":"Ventsislav Nikolov, Danko Naydenov, A. Antonov","doi":"10.1109/MCSI.2014.45","DOIUrl":null,"url":null,"abstract":"In this paper an implemented software system for identification of best fitting distribution of sample data is described. Some modifications and additions of the known statistical approaches are presented aiming the practical application of the distribution identification task. Additionally the cloud computing approach is applied in order to process the sample data series in parallel that makes significantly faster the implemented system.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Statistical Distribution Identification with Cloud Based Module\",\"authors\":\"Ventsislav Nikolov, Danko Naydenov, A. Antonov\",\"doi\":\"10.1109/MCSI.2014.45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper an implemented software system for identification of best fitting distribution of sample data is described. Some modifications and additions of the known statistical approaches are presented aiming the practical application of the distribution identification task. Additionally the cloud computing approach is applied in order to process the sample data series in parallel that makes significantly faster the implemented system.\",\"PeriodicalId\":202841,\"journal\":{\"name\":\"2014 International Conference on Mathematics and Computers in Sciences and in Industry\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Mathematics and Computers in Sciences and in Industry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MCSI.2014.45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCSI.2014.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical Distribution Identification with Cloud Based Module
In this paper an implemented software system for identification of best fitting distribution of sample data is described. Some modifications and additions of the known statistical approaches are presented aiming the practical application of the distribution identification task. Additionally the cloud computing approach is applied in order to process the sample data series in parallel that makes significantly faster the implemented system.
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