Forecasting Student Admission in Colleges with Neural Networks

In this study, the use of neural networks in predicting the performance of college at the admission counseling, before the actual event takes place, is analyzed. In our model, we aim to convert this forecasting problem into a classification one, i.e., a college based on its its total no. of seats filled during the counseling is classified in one of the five output categories chosen. This model can be used as a powerful decision aid by the university management, the individual college management & the anticipating students. We've presented the basic overview of ANN followed by few words on forecasting. The input decision variables & the output classes have been clearly laid out.