Accurate forecasting of building energy consumption via a novel ensembled deep learning method considering the cyclic feature

Engineering

• Energy Building 100%
• Deep Learning Method 100%
• Deep Belief Network 80%
• Extreme Learning Machine 80%
• Support Vector Machine 60%
• Hybrid Model 40%
• Experimental Result 20%
• Feature Vector 20%
• Energy Consumption Data 20%
• Great Influence 20%

Keyphrases

• Building Energy Consumption 100%
• Deep Learning Methods 100%
• Extreme Learning Machine 33%
• Least Squares Support Vector Regression (LSSVR) 25%
• Stochastic Component 25%
• Deep Belief Network 25%
• Novel Hybrids 16%
• Existing Data 8%
• Feature Vector 8%
• Spectral Analysis 8%
• Prediction Accuracy 8%
• World-building 8%
• Energy Consumption Data 8%
• Model of Models 8%
• Ensemble Model 8%
• Stable Components 8%
• Regression Vectors 8%
• Short-term Forecasting 8%
• Networked Learning 8%
• Forecast Performance 8%
• Building Energy Prediction 8%
• Cyclical Components 8%