Assylkhan Aitimbetov

A General Regression Neural Network Model for Predicting Shale Oil Content Using a Global Dataset of Diverse Oil Shale Deposits

Conventional methods for determining shale oil content are costly and time-consuming when large numbers of samples must be analyzed. This study developed and evaluated a general regression neural network (GRNN) to predict shale oil content using a compiled global dataset comprising 94 oil-shale observations. Following...