Application of Artificial Neural Networks for Corrosion Behavior of Ni–Zn Electrophosphate Coating on Galvanized Steel and Gene Expression Programming Models - Zeraati, Malihe; Abbasi, Hossein; Ghaffarzadeh, Parvin; Chauhan, Narendra Pal Singh; Sargazi, Ghasem (Frontiers in Materials, 2022)
Zn–Ni electrophosphate coating is one of the most commonly used materials in industrial applications. Corrosion resistance of this coating is very important in order to achieve the minimum corrosion current of the Zn–Ni electrophosphate coating. This paper described a new reliability simulation framework to determine the corrosion behavior of coating using gene artificial neural network (ANN) to estimate the corrosion current of the coating. The input parameters of the model are temperature, pH of electroplating bath, current density and Ni2+ concentration and corrosion current defines as output. The effectiveness and accuracy of the model was checked by utilizing absolute fraction of variance (R2=0.9999), mean absolute percentage error (MAPE=0.0171) and root mean square error (RMSE= 0.0002). The determined using genetic algorithm (GA) and the optimum practice condition are proposed.