Research on Container Demand Prediction of Wuhan Port Group Based on Bayesian Optimization
China's port logistics industry shows significant growth potential,which brought many market opportunities. Accurate demand forecasting has become crucial for strategic planning. This study constructs an evaluation index system from four dimensions of economic development,regional trade,transportation technology,and port capacity. Using Bayesian-optimized LSTM model,BP neural network,and random forest,the container throughput of Wuhan Port Group from 2011 to 2021 is predicted. Results show that the LSTM model achieves the highest accuracy. This study provides effective forecasting tools to help Wuhan Port Group meet future challenges and achieve sustainable growth.
万方数据
维普
