Prediction of amount of imports based on adaptive neuro-fuzzy inference system

被引:3
|
作者
Chang, Zhipeng [1 ]
Liu, Liping [1 ]
Li, Zhiping [1 ]
机构
[1] Anhui Univ Technol, Sch Econ, Maanshan 243002, Peoples R China
关键词
D O I
10.1109/IPC.2007.36
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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.
引用
收藏
页码:437 / 440
页数:4
相关论文
共 50 条
  • [41] ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR END MILLING
    Markopoulos, Angelos P.
    Georgiopoulos, Sotirios
    Kinigalakis, Myron
    Manolakos, Dimitrios E.
    [J]. JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY, 2016, 11 (09) : 1234 - 1248
  • [42] Diagnosing Breast Cancer Based on the Adaptive Neuro-Fuzzy Inference System
    Chidambaram, S.
    Ganesh, S. Sankar
    Karthick, Alagar
    Jayagopal, Prabhu
    Balachander, Bhuvaneswari
    Manoharan, S.
    [J]. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2022, 2022
  • [43] A damage assessment model based on adaptive neuro-fuzzy inference system
    Wu, Zheng-Long
    Zhao, Zhong-Shi
    [J]. Binggong Xuebao/Acta Armamentarii, 2012, 33 (11): : 1352 - 1357
  • [44] State of charge estimation based on adaptive neuro-fuzzy inference system
    Guan Jiansheng
    Xu Wenjin
    Zhang Abu
    [J]. ICCSE'2006: Proceedings of the First International Conference on Computer Science & Education: ADVANCED COMPUTER TECHNOLOGY, NEW EDUCATION, 2006, : 840 - 843
  • [45] Adaptive neuro-fuzzy inference system for modelling and control
    Amaral, TGB
    Crisóstomo, MM
    Pires, VF
    [J]. 2002 FIRST INTERNATIONAL IEEE SYMPOSIUM INTELLIGENT SYSTEMS, VOL 1, PROCEEDINGS, 2002, : 67 - 72
  • [46] Adaptive Neuro-Fuzzy Inference System for Financial Evaluation
    Orhei, Dragomir
    [J]. VISION 2020: SUSTAINABLE GROWTH, ECONOMIC DEVELOPMENT, AND GLOBAL COMPETITIVENESS, VOLS 1-5, 2014, : 241 - 245
  • [47] Adaptive Neuro-Fuzzy Inference System for drought forecasting
    Ulker Guner Bacanli
    Mahmut Firat
    Fatih Dikbas
    [J]. Stochastic Environmental Research and Risk Assessment, 2009, 23 : 1143 - 1154
  • [48] Adaptive Neuro-Fuzzy Inference System for Classification of Texts
    Kamil, Aida-zade
    Rustamov, Samir
    Clements, Mark A.
    Mustafayev, Elshan
    [J]. RECENT DEVELOPMENTS AND THE NEW DIRECTION IN SOFT-COMPUTING FOUNDATIONS AND APPLICATIONS, 2018, 361 : 63 - 70
  • [49] Edge Detection by Adaptive Neuro-Fuzzy Inference System
    Zhang, Lei
    Xiao, Mei
    Ma, Jian
    Song, Hongxun
    [J]. PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9, 2009, : 1774 - 1777
  • [50] Hysteresis Modeling with Adaptive Neuro-Fuzzy Inference System
    Mordjaoui, M.
    Chabane, M.
    Boudjema, B.
    Daira, R.
    [J]. FERROELECTRICS, 2008, 372 : 54 - 65