Modeling the Groundwater Level of the Miandoab Plain Using Artificial Neural Network Method and Election and Genetic Algorithms

It is very important to predicte and modifed the groundwater levels in the future period and the possibility of water resources planning and management to improve aquifer conditions. In this study, for the first time, used election algorithm to predicted groundwater level in the Miandoab plain. EA algorithm is a repeat algorithm inspired by presidential election and working with a set of khown solutions as a population. Also the results were compared of ANN and Genetic algorithm. Water table level data such as temperature, precipitation, humidity, evaporation and water surface data for the 2005 -2015 period was used as our data in this study. Based on the calculations performed and the results predicted from the statistical parameters, the election algorithm has a significant ability in the groundwater level with RMSE, R2 and NSE, 0.027, 0.93 and 0.74, respectively, in comparison to ANN method and GA algorithm and provides reliable results.