TS-Net: a spatial–temporal entanglement model for predicting the operational status of transmission towers
Authors:
- 10 February 2025
- journal article
- research article
- Published by Springer Nature in Electrical Engineering
- Vol. 107 (7) , 9369-9385
Abstract
No abstract availableKeywords
This publication has 43 references indexed in Scilit:
- Optimised SMOTE-based Imbalanced Learning for Student Dropout PredictionArabian Journal for Science and Engineering, 2024
- Application of convolutional neural networks based on Bayesian optimization to landslide susceptibility mapping of transmission tower foundationBulletin of Engineering Geology and the Environment, 2023
- Stacked LSTM for Short-Term Traffic Flow Prediction using Multivariate Time Series DatasetArabian Journal for Science and Engineering, 2022
- Multi-temporal-spatial-scale temporal convolution network for short-term load forecasting of power systemsApplied Energy, 2021
- Graph Attention Networks2020
- A novel deep learning method based on attention mechanism for bearing remaining useful life predictionApplied Soft Computing, 2020
- Landslide displacement prediction based on variational mode decomposition and WA-GWO-BP modelLandslides, 2019
- Method of operating a GIS‐based autopilot drone to inspect ultrahigh voltage power lines and its field testsJournal of Field Robotics, 2019
- A method for analyzing stability of tower-line system under strong windsAdvances in Engineering Software, 2019
- Dynamic Time Warping2007