Results 11 to 20 of about 30,162 (305)
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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Temperature prediction using fuzzy time series [PDF]
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2000 A drawback of traditional forecasting methods is that they can not deal with forecasting problems in which the historical data are represented by linguistic values. Using fuzzy time series to deal with forecasting problems can overcome this drawback. In this paper, we propose a new fuzzy time series model called the two-factors time-variant fuzzy time ...
Chen, S. M., Hwang, J. R.
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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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Rainfall Forecast in Different Methods of Trend Equations by Fuzzy Time Series
Ratio Mathematica, 2023 Fuzzy time series models have been put forward for Rainfall Prediction from many researchers around the globe. Fuzzy time series methods do not require any assumptions valid for classic time series approaches.
D Rajan, R Sugunthakunthalambigai
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Polynomial Fuzzy Information Granule-Based Time Series Prediction
Mathematics, 2022 Fuzzy information granulation transfers the time series analysis from the numerical platform to the granular platform, which enables us to study the time series at a different granularity. In previous studies, each fuzzy information granule in a granular
Xiyang Yang +3 more
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Time Series Analysis by Fuzzy Logic Methods
Algorithms, 2023 The method of analyzing data known as Discrete Mathematical Analysis (DMA) incorporates fuzzy mathematics and logic. This paper focuses on applying DMA to study the morphology of time series by utilizing the language of fuzzy mathematics.
Sergey M. Agayan +4 more
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Fuzzy time series analysis: Expanding the scope with fuzzy numbers
International Journal of Approximate Reasoning, 2023 Funding for open access charge: Universidad de Málaga ...
Hugo J. Bello +3 more
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E-Jurnal Matematika, 2023 Forecasting is a way to predict future events. One of the methods for forecasting is to use fuzzy time series Chen method. Fuzzy time series Chen is a development of fuzzy time series Song and Chissom method with more simplified arithmetic operations. In
ULYATIL AENI +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 ...
Yolcu, Ozge Cagcag, Lam, Hak-Keung
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