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Title
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Modeling short-term ground water level fluctuations using multi variate adaptive regression spline
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Type
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Presentation
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Keywords
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Ground water prediction, neuro-fuzzy with grid partition, multi variate adaptive regression spline
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Abstract
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The study investigates accuracy of two machine learning methods, neuro fuzzy system with grid partition (ANFIS-GP) and multi variate adaptive regression spline (MARS) in prediction of 1-day to 6-day ahead ground water levels (GWL) using data from two wells, USA. The outcomes indicate that the ANFIS-GP provides inferior results compared to regression based simple MARS method. The MARS method which is much simpler than the ANFIS-GP is recommended for short-term GWL prediction.
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Researchers
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Hadi Sanikhani (Second Researcher), Ozgur Kisi (First Researcher)
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