About this document
Hybrid CNN-LSTM for Transmission Faults by xNICKx is a document available to read on EtoBox.
This paper presents hybrid CNN-LSTM approaches for identifying and classifying transmission line faults using frequency response analysis (FRA). It evaluates the performance of various machine learning techniques, including support vector machine (SVM) and decision trees, in accurately detecting faults with different impedances. The proposed convolutional LSTM model demonstrates improved accuracy and early detection capabilities for high impedance faults compared to traditional methods.
- Author
- xNICKx
- Language
- EN