Advancing Predictive Accuracy in Heavy Metal Photocatalysis through Systematic Optimization of Neural Network Architectures
The efficiency of metal oxide photocatalysis is constrained by complex, nonlinear interactions among variables that are difficult to predict via traditional experimental methods. This study develops a robust Artificial Neural Network (ANN) model to identify the optimal training algorithm and architecture for predicting...