A Multi-Head Attention-Enhanced Fusion Model for Cross-Domain Short-Term Time Series Forecasting
The proposed multi-head attention fusion model (MAFM) provides an efficient, robust, and interpretable solution for time series forecasting tasks across multiple domains and demonstrates significant potential for practical applications in environmental monitoring, financial forecasting, and other real-world scenarios.