A Higher Order Mining Approach for the Analysis of Real-World Datasets

• Published in: Energies (Basel) Vol. 13; no. 21; p. 5781
• Main Authors: Abghari, Shahrooz, Boeva, Veselka, Brage, Jens, Grahn, Håkan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2020
• Subjects: Behavior; Clustering; clustering analysis; data mining; Datasets; district heating substations; Explicit knowledge; fault detection; Heat; higher order mining; Knowledge discovery; Methods; minimum spanning tree; outlier detection; Pattern recognition; Statistical process control; Subject specialists; Time series

In this study, we propose a higher order mining approach that can be used for the analysis of real-world datasets. The approach can be used to monitor and identify the deviating operational behaviour of the studied phenomenon in the absence of prior knowledge about the data. The proposed approach co...