Statistical and machine learning methods for Sensor Data

For maritime safety surveillance we develop new approaches
based on the availability of large arrays of sensors, which
monitor condition and performance of vessels, machinery, or
power systems.

We suggest new generic approaches to condition and/or performance monitoring, which is the process of identifying changes in sensor data that are indicative of a developing anomaly or fault.

Read more about the project (mn.uio.no)

Tags: Anomalies and changepoints, Approximate Bayesian Computing (ABC), Bayesian inference, Bayesian machine learning, Bayesian Model Averaging, Boosting, Clustering, Data fusion/integration, Deep learning/neural networks, Hidden Markov models, High dimensional inference, Hierarchical modeling, Model selection, Monte Carlo methods, Non-parametric and semi-parametric methods, Probabilistic programming, Real-time computing, State space models, Time series, Uncertainty quantification, Unsupervised learning, Statistical methods

Published July 3, 2023 4:27 PM - Last modified Oct. 23, 2023 1:33 PM