Article ID Journal Published Year Pages File Type
6923102 Computers & Geosciences 2013 13 Pages PDF
Abstract
► We predict water table depth fluctuations by using genetic programming (GEP). ► GEP results are compared with neuro-fuzzy (ANFIS) and neural networks (NN) methods. ► Comparison results show that the GEP models perform better than the other models. ► The precipitation is found to be an effective variable on water table depth.
Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
Authors
, , , , ,