乐胖代购免代理版

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With this development grows the need for versatile methods for mining industrial time series data. This paper introduces a practical approach for joint human-machine exploration of industrial time series data using the Matrix Profile, and presents some challenges involved. The approach is demonstrated on three real-life industrial data sets to show how it enables the user to quickly extract semantic information, detect cycles, find deviating patterns, and gain a deeper understanding of the time series. A benchmark test is also presented on ECG (electrocardiogram) data, showing that the approach works well in comparison to previously suggested methods for extracting relevant time series motifs.<\/jats:p>","DOI":"10.1007\/s10618-022-00871-y","type":"journal-article","created":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T09:05:02Z","timestamp":1664960702000},"page":"1-38","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Practical joint human-machine exploration of industrial time series using the matrix profile"],"prefix":"10.1007","volume":"37","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-4524-4204","authenticated-orcid":false,"given":"Felix","family":"Nilsson","sequence":"first","affiliation":[]},{"given":"Mohamed-Rafik","family":"Bouguelia","sequence":"additional","affiliation":[]},{"given":"Thorsteinn","family":"R\u00f6gnvaldsson","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,5]]},"reference":[{"issue":"6","key":"871_CR1","doi-asserted-by":"publisher","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","volume":"19","author":"H Akaike","year":"1974","unstructured":"Akaike H (1974) A new look at the statistical model identification. 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