Paper Info
Title
Fuzzy time series forecasting method based on hesitant fuzzy sets.
Abstract
We propose a fuzzy time series forecasting method using hesitant fuzzy sets.An aggregation operator is also proposed to aggregate hesitant fuzzy elements.Hesitancy is introduced by using multiple fuzzification methods.University of Alabama enrollments and SBI share prices are forecasted.Performance of method is measured in terms of MSE and AFER. This study proposes a fuzzy time series forecasting method based on hesitant fuzzy sets for forecasting in the environment of hesitant information. The proposed method addresses the problem of establishing a common membership grade for the situation when multiple fuzzification methods are available to fuzzify time series data. An aggregation operator for aggregating hesitant information is also proposed in the study. The proposed method is implemented to forecast enrollment at University of Alabama and price of state bank of India (SBI) share at Bombay stock exchange (BSE), India. In both time series data are fuzzified with triangular fuzzy sets constructed using intervals of equal and unequal length. The performance of the proposed method in forecasting student enrollments and SBI share price is measured in terms of root mean square and average forecasting errors. Statistical validation and performance analysis is also carried out to validate the proposed forecasting method.
Year
DOI
Venue
2016
10.1016/j.eswa.2016.07.044
Expert Syst. Appl.
Keywords
Field
DocType
Fuzzy time series,Hesitant fuzzy set,Aggregation operator,Fuzzy logical relation,Time invariant,Forecasting
Data mining,Time series,Fuzzy classification,Defuzzification,Fuzzy set operations,Computer science,Fuzzy logic,Fuzzy set,Fuzzy number,Type-2 fuzzy sets and systems
Journal
Volume
Issue
ISSN
64
C
0957-4174
Citations 
PageRank 
References 
10
0.50
29
Authors
2
Name
Order
Citations
PageRank
Kamlesh Bisht1100.50
Sanjay Kumar21034.18