Forecasting e-waste recovery scale driven by seasonal data characteristics: A decomposition-ensemble approach

Keyphrases

• Data Characteristics 100%
• Electronic Waste (E-waste) 100%
• Recovery Scale 100%
• Decomposition-ensemble 100%
• Seasonal Data 100%
• Waste Recovery 100%
• Scale-driven 100%
• E-waste Recycling 75%
• Single Model 50%
• Holt-Winters 50%
• Seasonal Component 50%
• Prediction Results 50%
• Support Vector Regression Model 50%
• Production Capacity 25%
• Forecast Error 25%
• Circular Economy 25%
• Time Series Forecasting 25%
• Model Vectors 25%
• Modelling Requirements 25%
• Subsidy Policy 25%
• Scale Prediction 25%
• Seasonal Autoregressive Integrated Moving Average Model 25%
• Resource Recovery 25%
• Forecasting Framework 25%
• STL Model 25%
• Decomposition-integration 25%
• Linear Sum 25%
• Seasonal-trend Decomposition Procedure Based on Loess 25%
• Seasonal Decomposition 25%
• Forecasting Performance 25%
• Forecasting Results 25%

Earth and Planetary Sciences

• Waste Recovery 100%
• Electronic Waste 100%
• Time Series 60%
• Waste Recycling 60%
• Support Vector Machine 40%
• Development Plan 20%
• Circular Economy 20%

Engineering

• Data Characteristic 100%
• Support Vector Machine 50%
• Moving Average 25%
• Development Plan 25%
• Resource Recovery 25%
• Circular Economy 25%