We would like to note that Prof Dr. Haidar Jabbar Abid Nassar Al-Janabi, an Academic at Biomedical Engineering Department, has managed to publish a Scientific Research in the Field of Electrical Engineering entitled:
"An Algorithm for the Classification of Power Quality Disturbance Signals Using a Tunable-Q-Factor Wavelet Transform and Ensemble Learning Methodology"
The Research has been published in the Journal of Electrical Engineering, a Worldwide Journal with a high Impact Factor within SCOPUS and Clarivate Engines, being part of the Publishing House Springer.
We should note as well that the Research has been conducted in cooperation with a Distinguished Group of Researchers from University of Babylon and University of Basra.
However, the Research has aimed to develop a new Classification Method for unwanted disturbances in Voltage, Current, and Frequency Emissions that fully take into account the disturbances collected in Additive Gaussian Noise. It has utilized Classifiers based on Random Forest Algorithm as well as AdaBoost Algorithm so as to effectively classify twelve frequent PQD signals. An investigation has been carried out regarding several disturbances in the Power Signal, each associated with different levels of noise, with the aim of demonstrating the effectiveness of the Proposed Classification System when working under noisy conditions.
It has been noted that a comparative analysis of Classification Accuracy through the use of previously proposed techniques has clearly revealed Enhanced Performance. Indeed, the Research has concluded that the Proposed Ensemble Classification Model has showed exceptional performance in terms of Classification Accuracy, achieving a perfect score of 100%. These results do highlight the superior recognition performance within Ensemble Random Forest Classifier.
Finally, we are obliged to confirm that these achievements contribute to promoting the Reputation of Al-Mustaqbal University in general and College of Engineering in particular in the Fields of Scientific Research.
Research link:
https://link.springer.com/article/10.1007/s00202-024-02294-y
Journal link:
https://link.springer.com/journal/202