Improved algorithm for splitting raw data into training and test subsamples for MLP-based models.

Based on our previous work, an improved algorithm for splitting raw data into training and test subsamples was developed to predict the spatial distribution of chemical elements in the surface soil layer using artificial neural networks (ANNs). The algorithm takes into account various factors affecting the distribution of the modeled variable. The data was obtained during soil screening on the urbanized area of the Noyabrsk city. [ABSTRACT FROM AUTHOR]