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- MakaleAçık Erişim2024Scopus SJRQ2A comparison of the performance of different innovative trend assessment approaches for air temperature and precipitation data: an application to Elazığ Province (Turkey)
Acar, Ramazan
In this study, the temporal variability of monthly total precipitation and monthly average temperature data of Palu station were analyzed. In addition to statistical analysis such as Mann–Kendall (MK) and SR, innovative polygon trend analysis (IPTA), innovative trend analysis (ITA), and combination of Wilcoxon test and scatter diagram (CWTSD) methods were used in the study. A total of 24 trend analyses (for 12 months of precipitation and temperature data) were conducted for each method used for temperature and precipitation parameters in the study. Look-ing at the results of these methods, a decreasing trend was detected only in December for precipitation data, common to all methods. For temperature data, an increasing trend was detected only in February and March. With the application of the IPTA, an increasing trend in some months and a decreasing trend in other months were detected for the two parameters. The Wilcoxon test exhibits significant consistency with the MK and Spearman's Rho (SR) in terms of the statistical trend, according to the examination of temperature and precipitation data using the CWTSD approach, which is relatively recent. Furthermore, the visual trend analysis demonstrates high consistency between the NO-ITA and Sȩn-ITA approaches.
AtıfScopus23WoS20OpenAlex34
İncele - MakaleAçık Erişim2023Scopus SJRQ3Statistical Analysis and EEG Signal Filtering Using Design of Window Function Based on Optimization Methods
Serbet, Fatmanur; Kaya, Turgay
The window functions, which are widely used in Finite Impulse Response (FIR) digital filter design with the Fourier Series Methods, aim to eliminate the oscillations adversely affecting the filter performance that occur during the filter design. Window functions, which were developed with different methods in the literature, were designed with three different optimization techniques in this study. By using Particle Swarm Optimization (PSO), Grey Wolf Colony Optimization (GWCO), Cuckoo Search Optimization (CSO) algorithms, which are among current metaheuristic optimization methods, new window functions are designed for FIR digital filter design such that the designed new window functions have different window coefficients and design parameters. The difference of the designed window functions was analyzed with the Friedman and Wilcoxon tests, which are statistical data analysis methods, and the originality of the designed window functions was proven. FIR digital filters that can perform the same operation as the designed window functions have been produced and the results obtained by performing the filtering application of the EEG signal with the produced filters are presented in the study.
AtıfScopus9WoS6OpenAlex7İncele