Mulyankan: A prediction for student´s performance using Neural Network

Various models have been suggested to evaluate and study the problem solving and decision making techniques of students. In this work, the Artificial Neural Network is used to evaluate the performance of students of university. Artificial Neural Networks are massively interconnected networks in parallel of simple elements (usually adaptable), with hierarchic organization, which try to interact with the objects of the real world in the same way that the biological nervous system does. Some parameters are used as input variables for the algorithms to calculate the approximate performance of students. These outputs are compared and the algorithm with nearly accurate result is used for the further assessment. This work can be implemented for upgradation of admission procedure of the University, training and placement of students. Using this work a teacher can know about the weak students in the middle of the academic year and teacher can give more concern to weak students.