Shengli Liao

Interpretable Daily Inflow Forecasting Model via Cross-Attention Hybrid Neural Networks Integrated with SHAP Analysis

The case study for one-day-ahead forecasting indicates that the proposed framework achieves overall superior predictive performance relative to the benchmark methods according to six evaluation metrics and the Wilcoxon signed-rank test result, confirming the effectiveness of the proposed cross-attention fusion strategy and SHAP-guided input optimization.