Correction: Xin et al. A Method for Predicting Bottomhole Pressure Based on Data Augmentation and Hyperparameter Optimisation. Processes 2026, 14, 1194

There was an error in the original publication. The sentence “MSE decreased by approximately 69.1%” should be replaced with “RMSE decreased by approximately 55.6%” [1].

A correction has been made to Results and Discussion, Paragraph 10:

By introducing multi-head attention to the optimal fusion architecture CNN-BiGRU, the CNN-BiGRU-Multi-Head Attention model achieved the best results across the entire table. Compared to CNN-BiGRU, it delivered significant improvements: RMSE decreased by approximately 55.6%, MAE further decreased by about 46.4%, SMAPE decreased by approximately 45.6%, R² increased by 0.0368, and MDA increased by 5.18%. In the radar chart of attention models, it exhibited the largest coverage area, with more “extended” and balanced dimensions across all metrics. This demonstrated that multi-head attention can adaptively enhance the contribution of critical time steps/key features, significantly improving trend judgment capability (MDA) while reducing errors. Consequently, it proved more suitable for predicting bottomhole pressure under complex operating conditions.

There is also one minor correction. On the fourth sentence of Section 2.1. Framework for Deep Learning Models, “MSE” should be replaced with “RMSE”. This is an inadvertent typo that the authors failed to detect in previous checks.

The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.