Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm

• Main Authors: Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.
• Other Authors: 57212194331
• Format: Article
• Published: IOS Press BV 2025
• Subjects: Anomaly detection; Cluster analysis; Abnormality detection; Abnormality detection and adjustment; Apache mahout; Canopy algorithm; Hybrid (CKMA); K-mean algorithm; K-mean algorithms; Load data; Power load; Power load data; K-means clustering

Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. The study taps into Apache Hadoop's robust tools for data...