Bu çalışmanın amacı Genetik Evrimsel Programlama (GEP) ve Yapay Sinir Ağları (YSA) yöntemlerini kullanarak en uygun yağış tahmin modelini geliştirmektir. Söz konusu metotlar Türkiye’de Göller Bölgesinde yeralan Eğirdir’e düşen yağışı tahmin etmek için kullanılmışlardır. Eğirdir’e ait yağış verileri aynı bölgede yeralan Isparta ve Senirkent istasyomlarının yağış verileri kullanılarak tahmin edilmiştir. Aylık yağış tahminleri için veriler Meteoroloji Genel Müdürlüğü’nden alınmıştır. Kullanılan meteorolojik veriler 1975 yılından 2010 yılına kadar olan 36 yıllık periyottan oluşmaktadır. GEP ve YSA modelleri için farklı girdi değişkenleri denenerek en uygun girdi seti elde edilmeye çalışılmıştır. Model sonuçları ile tarihi yağış kayıtları mukaye...
In the present study, gene expression programming (GEP) technique was used to develop one-month ahea...
Rainfall is one of the most challenging variables to predict, as it exhibits very unique characteris...
Regression problems provide some of the most challenging research opportunities in the area of machi...
Daily flow and suspended sediment discharge are two major hydrological variables that affect rivers’...
针对目前BP神经网络在实际应用中,网络结构难以确定以及网络极易陷入局部解问题,用遗传算法优化神经网络的连接权和网络结构,在遗传进化过程中采取保留最佳个体的方法,建立基于遗传算法的BP网络模型.同时通过...
This paper discusses the formation of an appropriate regression model in precipitation prediction. P...
Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Enerji Enstitüsü, 2019Thesis (M.Sc.) -- İstanbu...
Son zamanlarda artan küresel ısınmanın, atmosferdeki su yoğunluğunu artırdığı ve dolayısı ile yağış...
Drought forecasting is a vital task for sustainable development and water resource management. Emerg...
Analog methods (AMs) allow for the prediction of local meteorological variables of interest(predicta...
Early estimation of the drought may help reduce the potential adverse effects of drought. Indices de...
Analogue methods (AMs) rely on the hypothesis that similar situations, in terms of atmospheric circu...
AbstractWeather forecasting is complex and not always accurate, moreover, it is generally defined by ...
Regression problems provide some of the most challenging research opportunities in the area of machi...
Regression problems provide some of the most challenging research opportunities in the area of machi...
In the present study, gene expression programming (GEP) technique was used to develop one-month ahea...
Rainfall is one of the most challenging variables to predict, as it exhibits very unique characteris...
Regression problems provide some of the most challenging research opportunities in the area of machi...
Daily flow and suspended sediment discharge are two major hydrological variables that affect rivers’...
针对目前BP神经网络在实际应用中,网络结构难以确定以及网络极易陷入局部解问题,用遗传算法优化神经网络的连接权和网络结构,在遗传进化过程中采取保留最佳个体的方法,建立基于遗传算法的BP网络模型.同时通过...
This paper discusses the formation of an appropriate regression model in precipitation prediction. P...
Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Enerji Enstitüsü, 2019Thesis (M.Sc.) -- İstanbu...
Son zamanlarda artan küresel ısınmanın, atmosferdeki su yoğunluğunu artırdığı ve dolayısı ile yağış...
Drought forecasting is a vital task for sustainable development and water resource management. Emerg...
Analog methods (AMs) allow for the prediction of local meteorological variables of interest(predicta...
Early estimation of the drought may help reduce the potential adverse effects of drought. Indices de...
Analogue methods (AMs) rely on the hypothesis that similar situations, in terms of atmospheric circu...
AbstractWeather forecasting is complex and not always accurate, moreover, it is generally defined by ...
Regression problems provide some of the most challenging research opportunities in the area of machi...
Regression problems provide some of the most challenging research opportunities in the area of machi...
In the present study, gene expression programming (GEP) technique was used to develop one-month ahea...
Rainfall is one of the most challenging variables to predict, as it exhibits very unique characteris...
Regression problems provide some of the most challenging research opportunities in the area of machi...