Advances in Energy Forecasting and Infrastructure Monitoring

The field of energy forecasting and infrastructure monitoring is rapidly advancing with the development of new deep learning models and techniques. Researchers are exploring the use of wavelet transforms, graph attention, and neural ordinary differential equations to improve the accuracy and interpretability of energy forecasting models. Additionally, there is a growing interest in using drive-by vibration response signals for infrastructure health monitoring, with novel frameworks such as WaveletInception-BiLSTM networks showing promising results. The use of asynchronous cross-border market data is also being investigated to improve day-ahead electricity price forecasting in European markets. Noteworthy papers in this area include:

  • Wavelet-Enhanced Neural ODE and Graph Attention for Interpretable Energy Forecasting, which introduces a neural framework that integrates continuous-time Neural Ordinary Differential Equations and graph attention for energy forecasting.
  • IDS-Net: A novel framework for few-shot photovoltaic power prediction, which proposes a novel interpretable dynamic selection network based on feature information fusion.
  • WaveletInception Networks for Drive-by Vibration-Based Infrastructure Health Monitoring, which presents a novel deep learning-based framework for infrastructure health monitoring using drive-by vibration response signals.

Sources

Hashing for Fast Pattern Set Selection

Optimizing Basis Function Selection in Constructive Wavelet Neural Networks and Its Applications

Effective Self-Attention-Based Deep Learning Model with Evolutionary Grid Search for Robust Wave Farm Energy Forecasting

Wavelet-Enhanced Neural ODE and Graph Attention for Interpretable Energy Forecasting

Automatic Road Subsurface Distress Recognition from Ground Penetrating Radar Images using Deep Learning-based Cross-verification

Globalization for Scalable Short-term Load Forecasting

IDS-Net: A novel framework for few-shot photovoltaic power prediction with interpretable dynamic selection and feature information fusion

WaveletInception Networks for Drive-by Vibration-Based Infrastructure Health Monitoring

Leveraging Asynchronous Cross-border Market Data for Improved Day-Ahead Electricity Price Forecasting in European Markets

Built with on top of