An Adaptive Multiscale Ensemble Learning Paradigm for Nonstationary and Nonlinear Energy Price Time Series Forecasting

Computer Science

• Ensemble Learning 100%
• Kernel Function 100%
• least square support vector machine 50%
• empirical mode decomposition 50%
• Function Prototype 50%
• Particle Swarm Optimization 25%
• reconstruction algorithm 25%
• Prediction Accuracy 25%
• particle swarm optimization algorithm 25%
• Frequency Component 25%
• Moving Average 25%
• Directional Prediction 25%

Engineering

• Energy Engineering 100%
• Multiscale 100%
• Particle Swarm Optimization 40%
• Support Vector Machine 40%
• Least Square 40%
• Function Prototype 40%
• Model Parameter 20%
• High-Frequency Component 20%
• Moving Average 20%
• End Effect 20%
• Directional Prediction 20%