• DocumentCode
    2864275
  • Title

    Prediction of Amount of Imports Based on Adaptive Neuro-Fuzzy Inference System

  • Author

    Chang, Zhipeng ; Liu, Liping ; Li, Zhiping

  • Author_Institution
    Anhui Univ. of Technol., Maanshan
  • fYear
    2007
  • fDate
    11-13 Oct. 2007
  • Firstpage
    437
  • Lastpage
    440
  • Abstract
    In this paper, Adaptive network-based fuzzy inference system (ANFIS) was proposed to develop a predictive model for amount of imports. Aggregate import demand function was employed to select input variables. According to aggregate import demand function, the ANFIS model with five input variables and one output variable was built. To show ANFIS model has better ability than some other conventional statistical methods in predicting economics problems, the ANFIS model results were compared with ARIMA model results. The verification of the proposed model was achieved through wave characteristics time series plots and scatter diagrams. The experimental results show that the ANFIS has higher prediction accuracy than some other conventional statistical methods.
  • Keywords
    economic forecasting; inference mechanisms; ANFIS model; adaptive neuro-fuzzy inference system; aggregate import demand function; economics problem prediction; predictive model; statistical methods; Accuracy; Adaptive systems; Aggregates; Economic forecasting; Fuzzy neural networks; Fuzzy systems; Input variables; Predictive models; Scattering; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Pervasive Computing, 2007. IPC. The 2007 International Conference on
  • Conference_Location
    Jeju City
  • Print_ISBN
    978-0-7695-3006-2
  • Type

    conf

  • DOI
    10.1109/IPC.2007.36
  • Filename
    4438471