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A new fuzzy time series model based on robust clustering for forecasting of air pollution
(Elsevier Science Bv, 2018)
In this study, a new Fuzzy Time Series (FTS) model based on the Fuzzy K-Medoid (FKM) clustering algorithm is proposed in order to forecast air pollution. FTS models generally have some advantages when compared with other ...
A New Fuzzy Time Series Model Based on Fuzzy C-Regression Model
(Springer, 2018)
This study proposes a new fuzzy time series model based on Fuzzy C-Regression Model clustering algorithm (FCRMF). There are two major superiorities of FCRMF in comparison with existing fuzzy time series model based on fuzzy ...
Dynamic panel fuzzy time series model and its application to econometric time series
(Elsevier, 2021)
This study proposes a new Fuzzy Time Series (FTS) approach, called as Dynamic Panel Fuzzy Time Series (DPFTS) which combines Dynamic Panel Data Analysis and FTS. The major advantages of proposed approach can be summarized ...
Forecasting TRY/USD Exchange Rate with Various Artificial Neural Network Models
(Assoc Information Communication Technology Education & Science, 2017)
Exchange rate forecasting is one of the most common subjects among the forecasting problem field. Researchers and academicians from many different disciplines proposed various approaches for better exchange rate forecasting. ...
Forecasting COVID19 Reliability of the Countries by Using Non-Homogeneous Poisson Process Models
(Springer, 2022)
Reliability is the probability that a system or a product fulfills its intended function without failure over a period of time and it is generally used to determine the reliability, release and testing stop time of the ...