Application of Artificial Intelligence for Reservoir Storage Prediction: A Case Study

Abstract

There are many relevant and interesting contributions using Artificial Intelligence (AI) based techniques, with different purposes. It has been used as an effective way for estimating the forecasted data of reservoir daily storage value. The efficiency of various AI methods was explored in this article and later the best method is selected for reservoir storage level prediction. In estimating reservoir storage levels several regression algorithms and artificial neural network (ANN) approaches have been evaluated. There is better agreement between the ANN model compared to regression algorithms. The findings were demonstrated by significant correlation coefficient (R2) rate among the expected and calculated training outcome variables up to 0.91 and the highest validity outcome of Root Mean Square Error (RMSE) was 5.1989. Consequently, this method is therefore adequate for robustness and generalizability abilities and is ideal for forecasts.