Data-Driven Approaches for Prediction and Classification of Building Energy Consumption

Keyphrases

• Building Energy Consumption 100%
• Data-driven Approach 100%
• Building Classification 100%
• Load Forecasting 50%
• Building Energy Analysis 50%
• Energy Reduction 25%
• Support Vector Machine 25%
• Artificial Neural Network 25%
• Genetic Algorithm 25%
• K-means 25%
• Customer Demand 25%
• Energy Use 25%
• Network Support 25%
• Urban Sustainability 25%
• Long-term Strategy 25%
• Renewable Energy Technologies 25%
• Scale Change 25%
• Granularity 25%
• Energy Consumption Pattern 25%
• Existing Challenges 25%
• Building Envelop 25%
• Physical Data 25%
• Building Stock 25%
• Data-driven Algorithm 25%
• Hierarchical Clustering 25%
• Statistical Regression 25%
• Regression Decision Trees 25%
• Energy-related Applications 25%
• Building Energy 25%
• Self-organizing Clustering 25%
• Retrofit Strategies 25%
• Pattern Profiling 25%
• Decision Tree Algorithm 25%
• Energy Data 25%
• Regional Energy Consumption 25%
• Technical Characteristics 25%

Engineering

• Energy Engineering 100%
• Energy Building 100%
• Retrofit 40%
• Building Energy Analysis 40%
• Tasks 20%
• Artificial Neural Network 20%
• Microscale 20%
• Support Vector Machine 20%
• Genetic Algorithm 20%
• Macroscale 20%
• Dwelling 20%
• Network Support 20%
• Building Stock 20%
• Related Application 20%
• Renewable Energy Technologies 20%
• Load Forecasting 20%
• Self-Organizing Map 20%
• Granularity 20%