Figure 2. (A) Schematic diagram of the research process of screening anode of SOEC using ML models; (B) Comparison of actual and predicted values by the model, and the residuals of each predicted value by comparing with the actual values in XGBoost model; (C) General schematic diagram of the gradient boosting decision tree algorithm; (D) Part of the predicted hydrated proton concentration results. SOEC: Solid oxide electrolysis cell; ML: machine learning.
All published articles are preserved here permanently:
https://www.portico.org/publishers/oae/We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.
By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection. See our privacy policy for more information on the use of your personal data.
