Abstract
In today’s era, use of Internet is essential in every aspect of life. It is believed that the students from all discipline as well as computer science background must be susceptible to the internet for effective learning. This paper especially focuses on the student’s usage of the Internet according academic perspective. The objective is to identify most affecting variables which deal with the causes and reasons of possible restriction on usage of the Internet by students. The study has deployed artificial neural network (ANN) model for taking anticipatory measures for predicting use of the Internet. The Levenberg–Marquardt Back Propagation algorithm was used for training with three layers. Optimal artificial neural network model is proposed as a final outcome. Experimentation was carried out in R software.
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Muley, A.A., Bhalchandra, P.U. (2019). Data Mining of Student’s Internet Utilization Through Artificial Neural Network. In: Saini, H., Sayal, R., Govardhan, A., Buyya, R. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 32. Springer, Singapore. https://doi.org/10.1007/978-981-10-8201-6_32
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DOI: https://doi.org/10.1007/978-981-10-8201-6_32
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