A new interval prediction methodology for short-term electric load forecasting based on pattern recognition

Ciencias ambientales y de la tierra

• pattern recognition 71%
• forecasting 49%
• methodology 36%
• prediction 31%
• energy technology 10%
• machine learning 9%
• confidence interval 8%
• alternative energy 8%
• artificial neural network 8%
• electricity 7%
• decision making 6%
• market 6%
• statistics 6%
• anomaly 6%
• demand 5%

Ingeniería y ciencia de los materiales

• Electric load forecasting 100%
• Pattern recognition 55%
• Uncertainty 9%
• Long short-term memory 9%
• Renewable energy resources 6%
• Statistics 5%
• Electricity 5%
• Machine learning 5%
• Decision making 5%
• Neural networks 4%