Univariant time series forecasting of agriculture load by using LSTM and GRU RNNs

Engineering

• Recurrent 100%
• Long Short-Term Memory 100%
• Moving Average 66%
• Load Forecasting 66%
• Deep Learning Method 66%
• Infrastructure 33%
• Energy Engineering 33%
• Electric Power Utilization 33%
• Demand Side 33%
• Demand Forecasting 33%
• Actual Power 33%
• Artificial Neural Network 33%

Earth and Planetary Sciences

• Time Series 100%
• Artificial Neural Network 33%

Keyphrases

• Generation Side 20%
• Generation Forecasting 20%
• Precise Time 20%
• Metering Infrastructure 20%