Abstract
In this study, we investigate the forecasting accuracy of motherboard shipments from Taiwan manufacturers. A generalized Bass diffusion model with external variables can provide better forecasting performance. We present a hybrid particle swarm optimization (HPSO) algorithm to improve the parameter estimates of the generalized Bass diffusion model. A support vector regression (SVR) model was recently used successfully to solve forecasting problems. We propose an SVR model with a differential evolution (DE) algorithm to improve forecasting accuracy. We compare our proposed model with the Bass diffusion and generalized Bass diffusion models. The SVR model with a DE algorithm outperforms the other models on both model fit and forecasting accuracy.
Original language | English |
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Pages (from-to) | 3850-3855 |
Number of pages | 6 |
Journal | Expert Systems with Applications |
Volume | 41 |
Issue number | 8 |
DOIs | |
State | Published - 15 06 2014 |
Externally published | Yes |
Keywords
- Differential evolution
- Generalized Bass diffusion model
- Particle swarm optimization
- Support vector regression