Predictive Multivariate Model Based on Neural Networks with Artificial Intelligence to Make Decisions in Admission Processes in Public Universities of Peru

Ponce-Sánchez C.F.; Canelo-Sotelo C.A. · International Journal of Intelligent Systems and Applications in Engineering (2024)

Resumen

This study presents a predictive multivariate model based on neural networks with artificial intelligence for decision making in admission processes in public universities in Peru. The model has proven highly accurate in classifying applicants' grades, which highlights its effectiveness in decision-making in admissions processes. However, the importance of continuously addressing the quality and representativeness of the data used in the training of the model is highlighted to ensure unbiased results and avoid any bias or discrimination. It is suggested to carry out future research that focuses on the inclusion of diverse and representative data to achieve a more equitable and fair evaluation in the university admission processes.

Instituciones: Universidad Nacional de Ingeniería