mlsanityData to 14 Oct 2026

Time series Forecasting to detect anomalous behaviours in Multiphase Flow Meters

arXiv 2301.00014 ↗First posted 30 Dec 2022cs.LG cs.AIcited by 0

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Abstract (arXiv)

An Anomaly Detection (AD) System for Self-diagnosis has been developed for Multiphase Flow Meter (MPFM). The system relies on machine learning algorithms for time series forecasting, historical data have been used to train a model and to predict the behavior of a sensor and, thus, to detect anomalies.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 9 references that are in the map. First posted on arXiv 30 Dec 2022.

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3 of 9 references.

References · 3

  1. 2018An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modelingcited by 1,476
  2. 2018Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholdingcited by 410
  3. 2016Real-Time Anomaly Detection for Streaming Analyticscited by 5

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