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Öğe Basit ve Çoklu Regresyon Analizleri İle Kompaksiyon Parametrelerinin Tahmin Edilmesi ve F Testi İle Anlamlılığının İncelenmesi(E-Journal of New World Sciences Academy, 2020) Akyıldız, Hayrullah; Akbaş, ErgünKompaksiyon, nemli zeminin tabakalar halinde serilmesi, vibrasyon uygulayarak silindirlenmesi gibi işlemlerle sıkıştırılmasıdır. Kompaksiyon, gerek yol dolgularının gerek dolgu barajların sıklık kontrollerinin yapılması gerekse de diğer önemli mühendislik projelerinde yaygın olarak kullanılmaktadır. Dolayısıyla kompaksiyon parametrelerinin doğru olarak tespit edilmesi önem arz etmektedir. Şantiyelerde yeterli laboratuvar ekipmanının olmayışı ve işin bitiş süresinin kısıtlı olması, korelasyon denklemlerinin önemini arttırmıştır. Yeterli veri bulunması ve tolere edilebilecek güvenlik sınırları içerisinde sonuçlar elde edildiği takdirde, kompaksiyon parametrelerinin tahmininde istatistiğin kullanılması uygun görülmektedir. Bu durum hem ekonomik hem de zaman açısından bir kazanım sağlamaktadır. Çalışmada Adıyaman Balkar, Çelik ve Pınaryayla Göletlerinin zemin indeks özelliklerinin basit ve çoklu regresyon analizlerine tabi tutulmasıyla kompaksiyon parametreleri tahmin edilmeye çalışılmıştır. Önce göletlere ait zeminlerin verileri kullanılmış, ardından elek analizi neticesinde içinde sadece kil ve silt muhteva eden ince daneli zeminlerin indeks özellikleri değerlendirilmiş ve kompaksiyon parametreleri belirlenmeye çalışılmıştır. Mevcut verilerin istatistik olarak analizinin yapıldığı Eview programı yardımıyla basit ve çoklu regresyon analizleri yapılmış, elde edilen modellerin istatiksel olarak anlamlılığı F testi yapılarak incelenmiştir. Özellikle içeriğinde kum ve çakıl malzeme ihtiva etmeyen numunelere ait verilerin kullanılmasıyla diğer numune verilerine nazaran daha yüksek korelasyonların elde edildiği belirlenmiştir.Öğe Long-term meteorological and hydrological drought characteristics on the lower Tigris-Euphrates basin, Türkiye: relation, impact and trend(Springer Science and Business Media Deutschland GmbH, 2023) Eşit, Musa; Çelik, Recep; Akbaş, ErgünThis study aims to provide a comprehensive analysis of meteorological and hydrological droughts in the lower Tigris-Euphrates basin, Türkiye over 12-month time scale using the standardized precipitation index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) and the standardized streamflow index (SDI). To evaluate monthly trends of the SPI, SPEI, and SDI series, Mann–Kendall (MK), Spearman Rho (SR), and innovative trend analysis (ITA) tests are employed. The intrinsic relationships between the hydrological and meteorological drought in the study area as well as the specifics of how the oscillation period changes over time can also be obtained via wavelet transform coherence (WTC), which can reveal essential information. The results of all trend tests performed a decreasing trend consistently at stations 17275, 17810, 17948, 17950, and 17968 for all months in terms of SPI. SPEI is more sensitive to trend detection than SPI when taking into account all trend testing. In addition, the three trend tests are found to be more consistent with each other when SPEI is compared to SPI. According to SDI, the ITA method is clearly superior to the other two methods for identifying hidden trends. The ITA method, for example, captures a considerably increasing/decreasing trend at stations E26A038 (January and February), E26A012 (January, February, and from May to December), and E26A033 (from June to December) despite MK and SR tests finding no significant trends at any of the stations. When considering the WTC, positive month signals are strongly correlated with 12-month periods, according to the majority of stations.Öğe Machine learning based evaluation of concrete strength from saturated to dry by non-destructive methods(Elsevier Ltd, 2023) Günaydın, Osman; Akbaş, Ergün; Özbeyaz, Abdurrahman; Güçlüer, KadirMachine learning (ML) techniques have been increasingly applied in various scientific fields, including non-destructive testing (NDT), to enhance efficiency and speed up data analysis. In this study, an approach that aims to predict the compressive strength and quality of concrete with NDT and ML algorithms is presented to provide a great advantage in terms of both time and cost and to shorten the long laboratory periods. In the study, we aimed to set up a laboratory environment for determining the strengths of concrete samples by using Schmidt hardness values from NDT, curing times, water contents, and ultrasonic velocities. The data obtained in the laboratory environment was subjected to machine learning algorithms in the next process. In the laboratory environment, which is the first stage of the study, because concrete can be found at a variety of humidity levels depending on where it is used, 63 concrete samples were exposed to curing for 7, 28, and 90 days. Then these samples were put through a pressure test and subsequently exposed to various moisture conditions, from saturated to dry. Thus, the moisture state of concrete samples was evaluated based on their dryness or saturation in tests conducted on concrete samples. Afterwards, the ultrasonic velocities and Schmidt hardness values of these samples were measured. In the second stage, the strengths of concrete samples were classified with LR, MLP, SVM, and k-NN algorithms, and high R values were achieved. As a result of the studies carried out, the best R value (0.89) was achieved in the k-NN algorithm. This study has demonstrated that concrete strength values may be approximated with the k-NN method at high levels using sparse data collected in a laboratory setting.Öğe Spatial and temporal variation of meteorological parameters in the lower Tigris–Euphrates basin, Türkiye: application of non-parametric methods and an innovative trend approach(IWA Publishing, 2023) Eşit, Musa; Çelik, Recep; Akbaş, ErgünIn this study, Mann–Kendall (MK), Spearman’s rho (SR), and innovative trend analysis with significance test (ITA-ST) are performed on about 53 years of meteorological parameters obtained from 23 meteorological stations located in the lower Tigris–Euphrates basin (LTEB), Türkiye. Finally, sequential Mann–Kendall (SMK) and Cusum tests are applied to detect any abrupt changes in annual time series. Results indicate that MK and SR demonstrate a significant trend in seven of the total annual precipitation series, and ITA-ST captures the existence of a significant trend in 21 of the 23 total annual precipitations. Three methods reveal that there is an increasing trend in both the annual mean temperature and the annual total evapotranspiration (EP). MK, SR, and ITA-ST capture a significant decreasing trend in the 10, 8, and 16 of the 23 annual mean relative humidity (RH) series, respectively. According to the findings, ITA-ST is more sensitive than the classical MK and SR methods. Cusum and SMK tests are detected the start of trend year 21.7 and 8.6% of annual total precipitation, 95.65 and 69.56% of annual mean temperature, 47.82 and 17.4% of total mean RH, and 95.65 and 69.56% of annual total EP time series, respectively. The Cusum test is found to be more sensitive than the SMK test.
