Implementing support vector regression with differential evolution to forecast motherboard shipments

Fu Kwun Wang, Timon Du*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

21 Scopus citations

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 languageEnglish
Pages (from-to)3850-3855
Number of pages6
JournalExpert Systems with Applications
Volume41
Issue number8
DOIs
StatePublished - 15 06 2014
Externally publishedYes

Keywords

  • Differential evolution
  • Generalized Bass diffusion model
  • Particle swarm optimization
  • Support vector regression

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