A Data-Driven Approach for Long-Term Building Energy Demand Prediction

Keyphrases

• Actual Energy Consumption 50%
• Building Energy Consumption 100%
• Building Energy Performance 50%
• Built Environment 50%
• Carbon Dioxide Emissions 50%
• Coefficient of Variation 50%
• Commercial Buildings 50%
• Data-driven Approach 100%
• Disclosure Policy 50%
• Energy Assessment 50%
• Energy Consumption 50%
• Energy Consumption Data 50%
• Energy Consumption Prediction 100%
• Energy Consumption Reduction 50%
• Energy Disclosure 100%
• Energy Issues 50%
• Energy Supply Strategy 50%
• Ensemble Machine Learning 50%
• Knowledge Gaps 50%
• Large Volumes of Data 50%
• Local Officials 50%
• Long-term Energy Demand 50%
• Neighborhood Features 100%
• New York City 50%
• Number of Cities 50%
• Performance Results 50%
• Physical Features 50%
• Policy Decisions 50%
• Population Growth 50%
• Prediction Method 50%
• Prediction Model 50%
• Rapid Urbanization 50%
• Residential Buildings 50%
• Strategy Choice 50%
• Supply Policy 50%
• Sustainable World 50%
• Temporal Variation 50%
• Urban Areas 50%

Engineering

• Building Energy Performance 100%
• Built Environment 100%
• Coefficient of Variation 100%
• Commercial Building 100%
• Energy Consumption Data 100%
• Energy Issue 100%
• Learning Algorithm 100%
• Policy Decision 100%
• Reduce Energy Consumption 100%
• Residential Building 100%
• Temporal Variation 100%
• Term Energy 100%