2019 IEEE International Conference on Industrial Technology (ICIT) 2019
DOI: 10.1109/icit.2019.8755209
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A LS-SVM based Approach for Turbine Engines Prognostics Using Sensor Data

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Cited by 2 publications
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“…AI-based methods can be divided into shallow machine learning algorithms and deep learning algorithms [4]. The shallow models used for RUL prediction include support vector machine (SVM) [15,31], random forest (RF) [33], decision tree (DT) [28], etc. Since the trend of the raw data is unclear and contains noise [14], it is necessary to extract features from the raw data before inputting the model.…”
Section: Introductionmentioning
confidence: 99%
“…AI-based methods can be divided into shallow machine learning algorithms and deep learning algorithms [4]. The shallow models used for RUL prediction include support vector machine (SVM) [15,31], random forest (RF) [33], decision tree (DT) [28], etc. Since the trend of the raw data is unclear and contains noise [14], it is necessary to extract features from the raw data before inputting the model.…”
Section: Introductionmentioning
confidence: 99%