{"title":"为大数据建造巴别塔","authors":"Adnan Mian, Richard Ronson","doi":"10.1109/ICPHM.2019.8819390","DOIUrl":null,"url":null,"abstract":"Big data are sets of information that are too large or complex to process by traditional means. Finding results that determine trends is like finding a needle in a haystack. The field of big data is constantly changing, as a result, new methods and techniques are being developed. One such area that has not received substantial attention is a comprehensive guide on how to build a system that can handle big data using deep learning. Big data has gained great traction and support, due to it being a method to discover new trends with machine learning and artificial intelligence. This guide provides some high level design considerations to build an integrated big data system for a theoretical ship that uses prognostics to determine Remaining Useful Life (RUL) of components.","PeriodicalId":113460,"journal":{"name":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Building the Tower of Babel for Big Data\",\"authors\":\"Adnan Mian, Richard Ronson\",\"doi\":\"10.1109/ICPHM.2019.8819390\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Big data are sets of information that are too large or complex to process by traditional means. Finding results that determine trends is like finding a needle in a haystack. The field of big data is constantly changing, as a result, new methods and techniques are being developed. One such area that has not received substantial attention is a comprehensive guide on how to build a system that can handle big data using deep learning. Big data has gained great traction and support, due to it being a method to discover new trends with machine learning and artificial intelligence. This guide provides some high level design considerations to build an integrated big data system for a theoretical ship that uses prognostics to determine Remaining Useful Life (RUL) of components.\",\"PeriodicalId\":113460,\"journal\":{\"name\":\"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPHM.2019.8819390\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPHM.2019.8819390","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Big data are sets of information that are too large or complex to process by traditional means. Finding results that determine trends is like finding a needle in a haystack. The field of big data is constantly changing, as a result, new methods and techniques are being developed. One such area that has not received substantial attention is a comprehensive guide on how to build a system that can handle big data using deep learning. Big data has gained great traction and support, due to it being a method to discover new trends with machine learning and artificial intelligence. This guide provides some high level design considerations to build an integrated big data system for a theoretical ship that uses prognostics to determine Remaining Useful Life (RUL) of components.