Browsing by Author "Aksit, Serhat"

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Citation - WoS: 4
Citation - Scopus: 4
Advanced Hybrid Machine Learning Methods for Predicting Rainfall Time Series: The Situation at the Kütahya Station in Türkiye
(Springer Heidelberg, 2025) Ilkentapar, Mucella; Citakoglu, Hatice; Talebi, Hamed; Akturk, Gaye; Spor, Pinar; Caglar, Yasin; Aksit, Serhat
Long-term variations in rainfall patterns, known as rainfall variability, have increasingly impacted ecological and socioeconomic systems, particularly in regions with high sensitivity. Consequently, accurate forecasting of rainfall at both short- and long-term time scales is essential, necessitating a comprehensive analysis of historical rainfall time series data collected from meteorological stations. In this study, K & uuml;tahya Province was selected as the study area, utilizing monthly rainfall data from its sole meteorological station spanning the period from 1960 to 2023. The dataset was partitioned into a training set (January 1960-March 2008) and a test set (April 2008-December 2023). Lagged rainfall values at t-1, t-2, and t-3 were used as input variables to predict rainfall at time t. The primary objective of this research is to assess the effectiveness of various preprocessing techniques in developing hybrid machine learning models for rainfall prediction. Gaussian Process Regression (GPR), Support Vector Machines, and Adaptive Neuro-Fuzzy Inference System were employed as machine learning methods. Furthermore, multiple signal decomposition techniques, including Complete Ensemble Empirical Mode Decomposition (CEEMD), Tunable Q-Factor Wavelet Transform, Empirical Mode Decomposition, Robust Empirical Mode Decomposition, Variational Mode Decomposition, Empirical Wavelet Transform, and Ensemble Empirical Mode Decomposition (EEMD), were utilized as preprocessing steps to enhance model performance. The predictive performance of the developed hybrid models was evaluated using various statistical measures. Among the evaluated models, the CEEMD-GPR hybrid model exhibited the best prediction performance with Coefficient of Determination (R2 = 0.998) and Nash-Sutcliffe Efficiency (NSE = 0.998) values close to 1, Mean Absolute Error (MAE = 1.42) and Mean Squared Error (RMSE = 1.79) values close to zero. These findings indicate that CEEMD demonstrated superior decomposition efficiency compared to the other six decomposition techniques. Additionally, the Kruskal-Wallis test conducted during the analysis phase yielded a statistical significance level of p > 0.05, confirming that the observed and predicted rainfall data originated from the same distribution. Consequently, the effectiveness and reliability of the proposed hybrid models for rainfall prediction were validated.
Citation - WoS: 7
Citation - Scopus: 9
The Effect of Spoilers on Flow Around Tandem Circular Cylinders
(Pergamon-Elsevier Science Ltd, 2023) Ilkentapar, Mucella; Aksit, Serhat; Acikel, Halil Hakan; Oner, Ahmet Alper
Examining the flow characteristics around the cylindrical elements, such as offshore (submarine) pipelines which can be used in single or multiple arrangements, has a prominent place in fluid mechanics. The use of spoilers for self-embedding of these structures has been a subject that researchers have studied for many years. In this study, (a) the flow around a cylinder without and with a spoiler and (b) the effect of adding spoiler(s) to the tandem cylinders on the flow was experimentally investigated. In these experiments, where the ratio of the distance between the cylinders to the cylinder diameter is 2, the Reynolds number is 14000, which remains in the subcritical region. Four experiments were performed: the smoke-wire method was used for flow visualization, aerodynamic force measurement, velocity measurement by hot-wire anemometer, and pressure measurement to determine the pressure distribution on the cylinders. Pressure, velocity, and force results were recorded with the time histories in this study for the first time. Experimental studies show that when a spoiler is added to a single cylinder, an opposing lift force acts on that and the drag force increases due to the enlargement of the lowpressure region at the wake of the cylinder. In a tandem situation, when the upstream cylinder has a spoiler, no drag force acts on the downstream cylinder. The forces exerted on the upstream cylinder are not affected by whether the downstream cylinder has a spoiler. In the case of the downstream cylinder with the spoiler, the fluctuations in the aerodynamic forces of the upstream cylinder decrease owing to the downstream cylinder with the spoiler. The force fluctuations are more in the downstream cylinder, and unlike other tandem and singlecylinder cases, the vortex shedding becomes complex.