论文标题
TSML（时间序列计算机学习）
TSML (Time Series Machine Learnng)
论文作者
论文摘要
在过去的几年中，工业部门看到了自动化带来的许多创新。此自动化固有的是用于状态监视和数据收集的传感器网络的安装。这些数据丰富的环境中的主要挑战之一是如何从这些大量数据中提取和利用信息，以检测异常，发现模式以减少下降和制造错误，减少能源使用，预测故障/失败，有效的维护时间表等，以解决这些问题，我们开发了TSML。它的技术基于使用轻质过滤器的管道作为构建块，以同时处理大量工业时间序列数据。
Over the past years, the industrial sector has seen many innovations brought about by automation. Inherent in this automation is the installation of sensor networks for status monitoring and data collection. One of the major challenges in these data-rich environments is how to extract and exploit information from these large volume of data to detect anomalies, discover patterns to reduce downtimes and manufacturing errors, reduce energy usage, predict faults/failures, effective maintenance schedules, etc. To address these issues, we developed TSML. Its technology is based on using the pipeline of lightweight filters as building blocks to process huge amount of industrial time series data in parallel.
