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Sensor time series data: functional segmentation for effective machine learning

机译:传感器时间序列数据:有效机器学习的功能分割

摘要

Feature engineering can be performed on time series data making the data easy to manipulate and accessible to business users for analysis according to existing best practices. A computer system can, after receiving time series data related to a device, contextualize the time series data based on business data related to the device from, for example, an enterprise resource planning database. The contextualized data can be windowed by a selected feature based on execution data related to the device from, for example, a manufacturing execution system database. The windowed data can be transformed into summary data using a time series transformation. The summary data can be easily manipulated by, for example, generating genetic maps of the segmented and transformed data for clustering or searching for anomalies and patterns in response to user requests or automatically.
机译:可以在时间序列数据上执行特征工程,使数据易于操纵和可访问的商业用户根据现有的最佳实践进行分析。计算机系统可以在接收到设备相关的时间序列数据之后,基于与设备相关的业务数据的时间序列数据从例如企业资源计划数据库相关。基于从例如制造执行系统数据库相关的,基于与设备相关的执行数据,可以由所选特征窗口窗口化数据。窗口数据可以使用时间序列变换转换为摘要数据。摘要数据可以通过例如生成分段和变换数据的基因映射来容易地操纵,以响应于用户请求或自动响应于异常和模式。

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