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- MakaleYalnız künye2025Scopus SJRQ1Median-Linear model for solar radiation estimation by comparison with ANFIS and Angström-Prescott methods
Acar, Ramazan; Saplıoğlu, Kemal; Güçlü, Yavuz Selim
This paper aims to propose a novel approach to estimating solar radiation in relation to sunshine duration. A hybrid Median-Linear (MedLin) model is presented including both the median value and the linear solar radiation equation. First stage is concerned with two-stage alternative of the proposed model with inputs and outputs exhibiting a seasonality structure and it is seasonally adjusted using median values. In the second stage, the linear equation for the difference values is determined with estimations the difference in solar radiation. Finally, the median value and the estimated difference value are added. Monthly total solar radiation values are estimated using monthly total sunshine duration data from Mardin, Adana, Bozova, Hakkari, Şırnak, and Van stations in Southeast of Türkiye for the application. The predictions of the MedLin approach are compared with the results of the Angström-Prescott, ANFIS, and Mean-Linear (MeanLin) models. As for the prediction of monthly total solar radiation data at Mardin and Hakkari stations, the proposed MedLin approach yields the best results compared to other methods with mean absolute percentage error 3.508% and 8.951%, respectively. Angström-Prescott model for Adana, MeanLin method for Bozova, ANFIS model for Şırnak, and MeanLin model for Van provided the best predictions with mean absolute percentage error 3.721%, 3.285%, 4.278%, and 13.101%, respectively. The results show that the MedLin technique proposed in this paper is useful for solar radiation estimation.
AtıfWoS1
İncele - MakaleYalnız künye2025Scopus SJRQ1Seasonally adjusted periodic time series for Mann-Kendall trend test
Güçlü, Yavuz Selim; Acar, Ramazan; Saplıoğlu, Kemal
In this study, temperature data trend analysis is conducted, which is thought to be influenced by global warming, climate change, and local factor impacts. The main objective of this paper is to obtain an acceptable autoregressive correlation value for the MK test. For this purpose, seasonality (periodicity) especially in monthly time series is adjusted. Autoregressive correlation and homogeneity test values decrease after seasonal adjusting, but reasonable results are not achieved. Then, prewhitening procedure is also applied to the seasonally adjusted data. This process resulted in the data becoming both homogeneous and free autoregressive correlation. The final version of the time series is suitable for the MK test. Furthermore, the time series are divided into different time intervals, and the efficacy of the method is investigated. The results demonstrated that the method is suitable for time series with less than 30 years of data. The study demonstrated that the proposed method enhances the reliability of the data. Also, multiplication by 12 (months) allows the MK test with Z score in place of the Student's t-test in short-term data sets. This suggested methodology can be used to identify MK trend conditions in monthly time series. The application is based on monthly and annual average temperature data between 1957 and 2022 from three stations within the Kızılırmak basin (Çankırı, Kırşehir, Sivas stations) and one station within Seyhan Basin (Adana station) in Türkiye. The test results exhibited a significant increasing trend.
AtıfScopus37WoS34OpenAlex41İncele - DüzeltmeAçık Erişim2025Scopus SJRQ1Correction: Median-Linear model for solar radiation estimation by comparison with ANFIS and Angström-Prescott methods (Modeling Earth Systems and Environment, (2025), 11, 5, (352), 10.1007/s40808-025-02554-1)
Acar, Ramazan; Saplıoğlu, Kemal; Güçlü, Yavuz Selim
The Funding information section was missing from this article and should have read ‘This research was supported by the Scientific Research Projects Coordination Unit of Istanbul Technical University under Project Number MGA-2025-46432’.The original article has been corrected.