[HTML][HTML] Deep learning methods utilization in electric power systems
The fast expansion of renewable energy sources, rising electricity demand, and the
requirement for improved grid dependability have made it necessary to create cutting-edge …
requirement for improved grid dependability have made it necessary to create cutting-edge …
Dual stream network with attention mechanism for photovoltaic power forecasting
The operations of renewable power generation systems highly depend on precise
Photovoltaic (PV) power forecasting, providing significant economic, and environmental …
Photovoltaic (PV) power forecasting, providing significant economic, and environmental …
Deep dive into hybrid networks: A comparative study and novel architecture for efficient power prediction
The prediction of electric power consumption (PC) and power generation (PG) plays an
important role in the management, trading, and storage of energy, and in saving resources …
important role in the management, trading, and storage of energy, and in saving resources …
Improving the efficiency of multistep short-term electricity load forecasting via R-CNN with ML-LSTM
Multistep power consumption forecasting is smart grid electricity management's most
decisive problem. Moreover, it is vital to develop operational strategies for electricity …
decisive problem. Moreover, it is vital to develop operational strategies for electricity …
Combining the transformer and convolution for effective brain tumor classification using MRI images
In the world, brain tumor (BT) is considered the major cause of death related to cancer,
which requires early and accurate detection for patient survival. In the early detection of BT …
which requires early and accurate detection for patient survival. In the early detection of BT …
Solar power prediction using dual stream CNN-LSTM architecture
The integration of solar energy with a power system brings great economic and
environmental benefits. However, the high penetration of solar power is challenging due to …
environmental benefits. However, the high penetration of solar power is challenging due to …
An IoT enable anomaly detection system for smart city surveillance
Since the advent of visual sensors, smart cities have generated massive surveillance video
data, which can be intelligently inspected to detect anomalies. Computer vision-based …
data, which can be intelligently inspected to detect anomalies. Computer vision-based …
[HTML][HTML] Multivariate solar power time series forecasting using multilevel data fusion and deep neural networks
Accurate forecasting of regional solar photovoltaic power (SPVP) generation is essential for
efficient energy management and planning. Existing approaches have shown the …
efficient energy management and planning. Existing approaches have shown the …
A trapezoid attention mechanism for power generation and consumption forecasting
Effective operation of smart grids relies on accurate forecasting models for renewable power
generation (RPG) and power consumption. The intermittent and unpredictable nature of …
generation (RPG) and power consumption. The intermittent and unpredictable nature of …
[HTML][HTML] Data-driven prediction models of photovoltaic energy for smart grid applications
Due to the low total cost of production, photovoltaic energy is a key component of installed
renewable energy worldwide. However, photovoltaic energy is volatile in nature as it …
renewable energy worldwide. However, photovoltaic energy is volatile in nature as it …