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time-series-data

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Forecast airline passenger demand using time series models like AR, ARMA, and LSTM to improve operations, optimize scheduling, enhance resource allocation, and streamline supply chain management through accurate demand predictions

  • Updated Dec 3, 2024
  • Jupyter Notebook

We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for produce an anomaly score. Then, we merge these two score and produce merged anomaly score as a result.

  • Updated Jan 9, 2022
  • Python

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