An artificial neural networks approach to model and predict the relationship between the grounding resistance and length of buried electrode in the soil

This paper presents a technique based on the development of an artificial neural network (ANN) model for modeling and predicting the relationship between the grounding resistance and length of an electrode buried in the soil based on experimental data. The results indicate the strong agreement between the model prediction and experimental values. The statistical analysis shows that the R2 values were 0.995 and 0.925 for the training and testing sets, respectively.