Forecasting Students’ Enrollment Using Neural Networks and Ordinary Least Squares Regression Models
M.N Egbo · Journal of Advanced Statistics · 2018
Based on the presentation of dynamic and nonlinear data forecast, we discuss the difference in two approaches, Multi-layer feed-forward artificial neural networks and ordinary least squares regression for students' enrolment forecast in FUTO, Nigeria.A simple procedure to include the Mean square error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) is proposed and tested.The result suggested that the Multi-Layer Feed-Forward Artificial Neural Networks provides better predictions for nonlinear and chaotic systems.