RBF Neural Networks Advance Port Congestion and Freight Rate Forecasting

Frontiers has published research on using radial basis function (RBF) neural networks to forecast port congestion and container freight rate dynamics. This approach represents an application of machine learning techniques to predict shipping cost and port performance variability, which could help supply chain teams anticipate cost fluctuations and plan operations more effectively.