Clustering algorithms are a class of unsupervised machine learning (ML) algorithms that
feature ubiquitously in modern data science, and play a key role in many learning-based …

The education sector has benefitted enormously through integrating digital technology
driven tools and platforms. In recent years, artificial intelligence based methods are being …

The use of algorithms for decision-making in higher education is steadily growing, promising
cost-savings to institutions and personalized service for students but also raising ethical …

The university admission process plays a pivotal role in shaping the future of aspiring
students. However, traditional methods of admission decisions often fall short in capturing …

This scientific article describes the development of a neuro-fuzzy system for predicting the
success of applicants in university entrance exams. In the study, the ANFIS model was used …

In the 21st century, University educations are becoming a key pillar of social and economic
life. It plays a major role not only in the educational process but also in the ensuring of two …

In this paper, we investigate the methods used to evaluate the admission chances of higher
education institutions'(HEI) entrants as a crucial factor that directly influences the admission …

The digitalization of educational processes has enabled the generation of large datasets
that can be used to improve processes in academic environments. One particular problem is …

Every year many students apply for graduate admission to different universities. To select an
applicant, each university has different selection criteria such as GRE score, CGPA …

Currently, the prediction of student admissions still uses conventional machine learning
algorithms where there is no algorithm for optimization. This study aims to produce a model …