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
Link To Document