scholarly journals Intuitionistic fuzzy set-based time series forecasting model via delegeration of hesitancy degree to the major grade de-i-fuzzification and arithmetic rules based on centroid defuzzification

2021 ◽  
Vol 1988 (1) ◽  
pp. 012014
Author(s):  
Nik Muhammad Farhan Hakim N B Alam ◽  
Nazirah Ramli ◽  
Ainun Hafizah Mohd
Keyword(s):  
Time Series ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Time Series Forecasting ◽  
Forecasting Model ◽  
Intuitionistic Fuzzy

scholarly journals Intuitionistic Fuzzy Time Series Forecasting Model Based on Intuitionistic Fuzzy Reasoning

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Ya’nan Wang ◽  
Yingjie Lei ◽  
Xiaoshi Fan ◽  
Yi Wang
Keyword(s):  
Time Series ◽  
Clustering Algorithm ◽  
Intuitionistic Fuzzy Set ◽  
Time Series Forecasting ◽  
Approximate Reasoning ◽  
Fuzzy Time Series ◽  
Stock Index ◽  
Forecasting Model ◽  
New Model ◽  
Intuitionistic Fuzzy

Fuzzy sets theory cannot describe the data comprehensively, which has greatly limited the objectivity of fuzzy time series in uncertain data forecasting. In this regard, an intuitionistic fuzzy time series forecasting model is built. In the new model, a fuzzy clustering algorithm is used to divide the universe of discourse into unequal intervals, and a more objective technique for ascertaining the membership function and nonmembership function of the intuitionistic fuzzy set is proposed. On these bases, forecast rules based on intuitionistic fuzzy approximate reasoning are established. At last, contrast experiments on the enrollments of the University of Alabama and the Taiwan Stock Exchange Capitalization Weighted Stock Index are carried out. The results show that the new model has a clear advantage of improving the forecast accuracy.

Multi-factor high-order intuitionistic fuzzy time series forecasting model

2016 ◽  
Vol 27 (5) ◽  
pp. 1054-1062 ◽  
Author(s):  
Ya'nan Wang ◽  
◽  
Yingjie Lei ◽  
Yang Lei ◽  
Xiaoshi Fan
Keyword(s):  
Time Series ◽  
Time Series Forecasting ◽  
High Order ◽  
Fuzzy Time Series ◽  
Forecasting Model ◽  
Intuitionistic Fuzzy

Intuitionistic Fuzzy Time Series Forecasting Based on Dual Hesitant Fuzzy Set for Stock Market

2019 ◽  
pp. 37-57
Author(s):  
Sanjay Kumar ◽  
Kamlesh Bisht ◽  
Krishna Kumar Gupta
Keyword(s):  
Time Series ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Time Series Data ◽  
Time Series Forecasting ◽  
Fuzzy Time Series ◽  
Hesitant Fuzzy Set ◽  
Series Data ◽  
Intuitionistic Fuzzy ◽  
Dual Hesitant Fuzzy Set

In this chapter, an application of dual hesitant fuzzy set (DHFS) in intuitionistic fuzzy time series forecasting is proposed to handle fuzziness and non-determinism that occurs due to multiple valid fuzzification method for time series data. Advantages of the proposed DHFS-based time series forecasting method are that it includes characteristics of both intuitionistic and hesitant fuzzy sets to handle the non-determinism and hesitancy corresponding to single membership grade multiple membership grades of an element. In the present study, universe of discourse is partitioned and fuzzified the time series data by two different fuzzification methods (triangular and Gaussian) to construct DHFS. Further, elements of DHFS are aggregated to construct the intuitionistic fuzzy sets. Proposed method is implemented over the share market prizes of SBI at BSE, India and SENSEX of BSE to confirm its out performance over existing time series forecasting methods using RMSE and AFER.

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