Machine learning for anomaly detection on intelligent transportation time series data
In intelligent transportation systems, machine learning approaches are presented to deal with time series anomaly detection. But there are always far more normal samples, making it suffer from unbalanced samples for traffic anomaly detection. In this dissertation, based on the state-of-the-art model...
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格式: | Thesis-Master by Coursework |
語言: | English |
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Nanyang Technological University
2022
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在線閱讀: | https://hdl.handle.net/10356/163318 |
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機構: | Nanyang Technological University |
語言: | English |