Prediction of Container Throughput at Yangluo Port Based on Exponential Smoothing Method and Grey GM (1,1) Model and Intelligent Decision Support

The exponential smoothing method and the grey GM (1,1) model are two research approaches in knowledge discovery and data mining. Over the past ten years, the container throughput of Yangluo Port has been increasing continuously. This study investigates the modeling and application of both methods using time series data on container throughput at Wuhan Yangluo Port from 2015 to 2024. Through comparison of error metrics between the two forecasting methods, it is found that the GM (1,1) model demonstrates superior prediction accuracy. The model can accurately forecast container throughput at Yangluo Port in subsequent years, thereby providing data support for intelligent decision-making systems in port development.