Mixed order single variable intuitionistic fuzzy time series forecasting method based on a new artificial neural network and grey wolf optimization algorithm [PDF]
Scientific ReportsThe ease of use of fuzzy time series methods and their success in forecasting performance have led to a rapid increase in research in this field. While classical fuzzy time series methods operate solely on membership values, intuitionistic fuzzy time ...
Turan Cansu, Eren Bas, Erol Egrioglu
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Adaptive Non-Stationary Fuzzy Time Series Forecasting with Bayesian Networks [PDF]
SensorsDespite its interpretability and excellence in time series forecasting, the fuzzy time series forecasting model (FTSFM) faces significant challenges when handling non-stationary time series.
Bo Wang, Xiaodong Liu
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Intuitionistic fuzzy time series functions approach for time series forecasting [PDF]
Granular Computing, 2020 AbstractFuzzy inference systems have been commonly used for time series forecasting in the literature. Adaptive network fuzzy inference system, fuzzy time series approaches and fuzzy regression functions approaches are popular among fuzzy inference systems.
Egrioglu, Erol, Bas, Eren, Yolcu, Ufuk
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Multilayer Stock Forecasting Model Using Fuzzy Time Series [PDF]
The Scientific World Journal, 2014 After reviewing the vast body of literature on using FTS in stock market forecasting, certain deficiencies are distinguished in the hybridization of findings.
Hossein Javedani Sadaei +1 more
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Cheng Fuzzy Time Series Model to Forecast the Price of Crude Oil in Malaysia
Journal of Computing Research and Innovation, 2022 Crude oil is one of the important commodities to Malaysia. As a producer and exporter of oil and gas, Malaysia has gained high Gross Revenue from this sector. Crude oil is the global commodity and highly demanded.
Jasmani Bidin +4 more
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A Three-Stage Nonparametric Kernel-Based Time Series Model Based on Fuzzy Data
Mathematics, 2023 In this paper, a nonlinear time series model is developed for the case when the underlying time series data are reported by LR fuzzy numbers. To this end, we present a three-stage nonparametric kernel-based estimation procedure for the center as well as ...
Gholamreza Hesamian +2 more
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A combined robust fuzzy time series method for prediction of time series [PDF]
Neurocomputing, 2017 Outlier(s) have an adverse impact on the performance of fuzzy time series models.We proposed a combined robust fuzzy time series model (C-R-FTSM).C-R-FTSM uses fuzzy inputs composed of membership values as well as the crisp data.Training process of C-R-FTSM is performed by PSO in a single optimization process.Huber's loss function based on M estimator ...
Ozge Cagcag Yolcu, Hak-Keung Lam
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Increasing and Decreasing with Fuzzy Time Series [PDF]
Advances in Intelligent Systems Research, 2006 There is a significant problem associated with the fuzzy time series. That is a strict increasing and decreasing case. Under the discussion case, fuzzy time series model arise a continuous increasing/decreasing forecasting value. From the illustrative example, we can see that our definition not only define the trend of the fuzzy numbers that represent ...
Ming-Tao Chou, Hsuan-Shih Lee
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Average-Based Fuzzy Time Series Markov Chain Based on Frequency Density Partitioning
Journal of Applied Mathematics, 2023 Fuzzy time series (FTS) is one of the forecasting methods that has been developed until now. The fuzzy time series is a forecasting method that uses the concept of fuzzy logic, which Song and Chissom first introduced.
Susilo Hariyanto +3 more
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Forecasting Indonesian Oil, Non-Oil and Gas Import Export with Fuzzy Time Series
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2022 Indonesia is active in export and import activities. Some of the commodities traded are oil and gas, as well as food and other industrial materials. Export and import activities play a role in determining the stability of the country's economy seen from ...
Syalam Ali Wira Dinata +2 more
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