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TIME-SERIES FAULT DETECTION, FAULT CLASSIFICATION, AND TRANSITION ANALYSIS USING A K-NEAREST-NEIGHBOR AND LOGISTIC REGRESSION APPROACH
TIME-SERIES FAULT DETECTION, FAULT CLASSIFICATION, AND TRANSITION ANALYSIS USING A K-NEAREST-NEIGHBOR AND LOGISTIC REGRESSION APPROACH
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机译：使用k离邻邻和逻辑回归方法的时间序列故障检测，故障分类和转换分析
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摘要
Methods and systems for time series transient analysis of data are disclosed herein. The method includes receiving time series data; Generating a training data set comprising randomized data points; Generating randomized data point combinations using the set of randomized data points, within a time window; Computing distance values based on the randomized data point combinations; Generating a classifier based on the plurality of computed distance values; And using the classifier, determining a probability that the new time series data generated during the new execution of the process will match the time series data. A system for performing the method is also disclosed.
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