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Predicting the subscribers of fixed-line and cellular phone in Japan by a novel prediction model

Author

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  • Li, Guo-Dong
  • Masuda, Shiro
  • Nagai, Masatake

Abstract

In this paper, a novel grey prediction model is proposed to enhance the performance of prediction for the amount of fixed-line and cellular phone subscribers in Japan. The cubic spline function is first integrated into grey prediction model to enhance its prediction capability. Then the particle swarm optimization (PSO) algorithm is applied, so that the prediction performance can be improved further. The prediction results using proposed models are very satisfactory.

Suggested Citation

  • Li, Guo-Dong & Masuda, Shiro & Nagai, Masatake, 2014. "Predicting the subscribers of fixed-line and cellular phone in Japan by a novel prediction model," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 321-330.
    • Handle: RePEc:eee:tefoso:v:81:y:2014:i:c:p:321-330
    DOI: 10.1016/j.techfore.2013.05.004
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    References listed on IDEAS

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    1. Zhao, Ze & Wang, Jianzhou & Zhao, Jing & Su, Zhongyue, 2012. "Using a Grey model optimized by Differential Evolution algorithm to forecast the per capita annual net income of rural households in China," Omega, Elsevier, vol. 40(5), pages 525-532.
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    Cited by:

    1. Li, Guo-Dong & Masuda, Shiro & Nagai, Masatake, 2014. "The prediction for Japan's domestic and overseas automobile production," Technological Forecasting and Social Change, Elsevier, vol. 87(C), pages 224-231.
    2. Liu, Zhenkun & Jiang, Ping & De Bock, Koen W. & Wang, Jianzhou & Zhang, Lifang & Niu, Xinsong, 2024. "Extreme gradient boosting trees with efficient Bayesian optimization for profit-driven customer churn prediction," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    3. Harrison, Gillian & Thiel, Christian, 2017. "An exploratory policy analysis of electric vehicle sales competition and sensitivity to infrastructure in Europe," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 165-178.

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