Data Imputation Using Artificial Neural Network for a Reservoir System

This study provides a comprehensive comparison of the different algorithms implemented on a reservoir system, and the results are statistically analyzed from the results of other machine learning algorithms. Different weights and activation methods have been used to obtain the results. The algorithms implemented on the data of reservoir system are generative adversarial networks, synthetic model, non-dominated sorting genetic algorithm 2. Later on, we have done comparisons and visualization on the data obtained We have attempted to implement generative adversarial networks on a reservoir system that is in the time series representation and the data values are from June 1, 1989, to May 1, 2016. Data was collected from the reservoir authorities, and they did not have the records for some of the months. The target is to regenerate that empty values and find out what could be the next data value in the upcoming months.