Time-series forecasting using flexible neural tree model

  • Authors:
  • Yuehui Chen;Bo Yang;Jiwen Dong;Ajith Abraham

  • Affiliations:
  • School of Information Science and Engineering, Jinan University, 106 Jiwei Road, Jinan 250022, PR China;School of Information Science and Engineering, Jinan University, 106 Jiwei Road, Jinan 250022, PR China;School of Information Science and Engineering, Jinan University, 106 Jiwei Road, Jinan 250022, PR China;School of Information Science and Engineering, Jinan University, 106 Jiwei Road, Jinan 250022, PR China and School of Computer Science and Engineering, Chung-Ang University, Seoul, Republic of Kor ...

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2005

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Abstract

Time-series forecasting is an important research and application area. Much effort has been devoted over the past several decades to develop and improve the time-series forecasting models. This paper introduces a new time-series forecasting model based on the flexible neural tree (FNT). The FNT model is generated initially as a flexible multi-layer feed-forward neural network and evolved using an evolutionary procedure. Very often it is a difficult task to select the proper input variables or time-lags for constructing a time-series model. Our research demonstrates that the FNT model is capable of handing the task automatically. The performance and effectiveness of the proposed method are evaluated using time series prediction problems and compared with those of related methods.