Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/12605
Title: An improved fuzzy time series forecasting model using variations of data
Authors: Võ, Văn Tài
Keywords: Fuzzy time series
Abbasov-Mamedova
Population GDP
Vietnam
Issue Date: 2018
Series/Report no.: Fuzzy Optimization and Decision Making;1 .- p. 1-23
Abstract: This study proposes an improved fuzzy time series (IFTS) forecasting model using variations of data that can interpolate historical data and forecast the future. The parameters in this model are chosen by algorithms to obtain the most suitable values for each data set. The calculation of the IFTS model can be performed conveniently and efficiently by a procedure within the R statistical software that has been stored in the AnalyseTS package. The proposed model is also used in the forecasting of two real problems in Vietnam: the penetration of salt and the total population. These numerical examples show the advantages of the proposed model in comparison with existing models and illustrate its effectiveness in practical applications.
URI: http://dspace.ctu.edu.vn/jspui/handle/123456789/12605
Appears in Collections:Tạp chí quốc tế

Files in This Item:
File Description SizeFormat 
_file_1.46 MBAdobe PDFView/Open
Your IP: 3.238.147.211


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.