Table 5 Comparison of key component variants for multi horizon prediction on ETTm2 under the same backbone and training recipe. No JSD and KLD removes divergence based terms from module scoring and retains only normalized MSE and normalized MAE. Fixed threshold uses a single constant threshold shared by all modules and horizons, and the threshold is set as the median of warm up adaptive thresholds from the same run. Another fusion mode replaces weighted fusion with hard selection that copies parameters from the parent module with smaller module level fitness. Lower is better.

From: Hybrid evolutionary-gradient training improves long-term time series forecasting