DSPR decouples statistical temporal evolution from physics-informed residual dynamics via an adaptive window for transport delays and a physics-guided dynamic graph to achieve accurate, physically plausible forecasts on industrial benchmarks with over 99% mean conservation accuracy.
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DSPR: Dual-Stream Physics-Residual Networks for Trustworthy Industrial Time Series Forecasting
DSPR decouples statistical temporal evolution from physics-informed residual dynamics via an adaptive window for transport delays and a physics-guided dynamic graph to achieve accurate, physically plausible forecasts on industrial benchmarks with over 99% mean conservation accuracy.