مشخصات پژوهش

عنوان	Modeling short-term ground water level fluctuations using multi variate adaptive regression spline
نوع پژوهش	مقاله ارائه شده کنفرانسی
کلیدواژه‌ها	Ground water prediction, neuro-fuzzy with grid partition, multi variate adaptive regression spline
چکیده	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.
پژوهشگران	هادی ثانی خانی (نفر دوم)، ازگور کیشی (نفر اول)