Meteoroloji̇k Veri̇ler Kullanilarak Yeralti Su Sevi̇yesi̇ni̇n Geneti̇k Programlama İle Tahmi̇ni̇

Abstract

ÖZTatlı su ihtiyacının önemli bir kısmı yeraltı suları tarafından karşılanmaktadır. Bu nedenle yeraltı sularının kalitesinin ve miktarının izlenmesi ve mevcut durumunun ortaya konması su yönetimi politikalarının geliştirilmesi bakımından önemlidir. Genetik programlama (GP) evrimsel tabanlı bir yaklaşımdır ve son yıllarda alternatif bir yapay zeka tekniği olarak kullanılmaktadır. GP, diğer yapay zeka tekniklerine göre değişkenler arasındaki ilişkilerden faydalanarak problemin bir matematiksel modelini ortaya koyabilme avantajına sahiptir. ESTIMATION OF GROUNDWATER LEVEL WITH GENETIC PROGRAMMING USING METEOROLOGICAL DATA ABSTRACTThe significant portion of freshwater needs is met by ground water. Therefore, paying attention to the monitoring of groundwater quality and quantity data and to reveal the current situation is necessary for the calculation of the potential for water development and water management policies. Genetic programming (GP) is an evolutionary-based approach and is used as an alternative to artificial intelligence techniques in recent years. GP has the advantage of revealing a mathematical model by using the relationships between variables. In this study, various mathematical models have been developed to predict the groundwater levels by using meteorological data and previous days of groundwater levels. To the development of mathematical models, a new GP approach, multi-gene genetic programming (MGGP), was implemented. The daily data obtained from Karacaviran observation wells and Develi meteorological station covering the years of 2007-2009 were used for the creation of the models. The accuracy of the generated models to predict the ensuing a month (30 days) groundwater levels were evaluated and compared with the multiple linear regression models. The results * Corresponding author / Sorumlu yazar.