Manzura Irisbayeva’s Article in Scopus

An article by Manzura Nurmamatovna Irisbayeva, Associate Professor of the Department of Psychology and Social-Humanitarian Sciences, entitled “Optimized Machine Learning Models for Water Quality Prediction: Integrating Support Vector Machines and Random Forest through Nonlinear Functional Analysis” was published in the Q3-ranked journal Results in Nonlinear Analysis.

The research addresses the optimization of machine learning models for water quality prediction, particularly integrating Support Vector Machines and Random Forest algorithms based on nonlinear functional analysis.