Paper Info
Title
A Fuzzy Time Series Forecasting Method Induced By Intuitionistic Fuzzy Sets
Abstract
Intuitionistic fuzzy sets (IFSs) are well established as a tool to handle the hesitation in the decision system. In this research paper, fuzzy sets induced by IFS are used to develop a fuzzy time series forecasting model to incorporate degree of hesitation (nondeterminacy). To improve the forecasting accuracy, induced fuzzy sets are used to establish fuzzy logical relations. To verify the performance of the proposed model, it is implemented on one of the benchmarking time series data. Further, developed forecasting method is also tested and validated by applying it on a financial time series data. In order to show the accuracy in forecasting, the method is compared with other forecasting methods using different error measures.
Year
DOI
Venue
2015
10.1142/S1793962315500415
INTERNATIONAL JOURNAL OF MODELING SIMULATION AND SCIENTIFIC COMPUTING
Keywords
Field
DocType
Fuzzy time series, intuitionistic fuzzy sets, nondeterminacy, induced fuzzy set, data models
Data mining,Defuzzification,Fuzzy classification,Computer science,Fuzzy set operations,Fuzzy mathematics,Fuzzy set,Artificial intelligence,Type-2 fuzzy sets and systems,Fuzzy number,Membership function,Machine learning
Journal
Volume
Issue
ISSN
6
4
1793-9623
Citations 
PageRank 
References 
1
0.36
18
Authors
2
Name
Order
Citations
PageRank
Sanjay Kumar1392.49
Sukhdev Singh Gangwar2281.81