Fault Classification for Protection in MMC-HVDC Using Machine Learning Algorithms

Cevat Rahebi

The problems in MMC-HVDC protection systems are categorized in this study using machine learning algorithms. The voltage and current data were utilized to determine the classification's features. With the use of the features derived from the voltage and current, machine learning (ML) and artificial machine learning (ML) have produced a defect locator that is accurate enough. Using this data, simulations of various fault types and unknown locations at different system points were run to anticipate the outcomes. Metrics including specificity, accuracy, and sensitivity were used to evaluate the e ...Daha fazlası

Konferans Kağıdı 2023 IEEE Xplore 15 Görüntülenme Süresiz Ambargo

Süresiz Ambargo

Harris Hawks Optimization (HHO) Algorithm based on Artificial Neural Network for Heart Disease Diagnosis

Cevat Rahebi

Signal processing methods usually diagnose heart disease, and the diagnosis of this type of disease by signal processing sometimes encounters many difficulties. To reduce diagnostic problems, careful feature selection and training are needed to analyze these signals. In this study, an attempt has been made to combine machine learning skills, such as neural network learning, with the Harris Hawks Optimization method to diagnose heart disease. In this paper, the heart disease diagnosis is analyzed with the feature selection method. For feature selection, the Harris Hawks Optimization Algorithm b ...Daha fazlası

Bildiri 2021 IEEE 305 Görüntülenme Süresiz Ambargo