Comparison and evaluation of different clustering algorithms and methods to define weather event profiles and their characteristics
DOI:
https://doi.org/10.26034/lu.akwi.2023.4557Keywords:
Cluster analysis, Cluster models, Weather data, Meteorology, Clustering of weather data, Weather event profilesAbstract
Cluster analyses with the algorithms KMeans, HAC, GMM & DBSCAN on weather data from Ontario, Canada, using DSR. The goal is to identify weather-event-profiles. The profiles could be used in weather forecasts, dashboards and for anomaly detection. IBM provides seven years of historical weather data with potential for future research.
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