Effective Prediction in Amazon Web Service Based Clustered Data Using Artificial Neural Networks

Abstract

Now a days, there are number of cab services providers which are confusing the client with number of similar kind of service options. That's why there is a need of selecting a quality service from a set of given services. It motivates us to design an approach which is efficient in providing the effective service after the data analysis of real time data developed and collected through Amazon Web Services. This paper aims at analyzing a mathematical model that is used to predict the most efficient output of a dataset of a model using Artificial Neural Network. The proposed mathematical model is made and applied on a database of real time cab services developed using Amazon Web Services to predict the effective web service. We have analyzed the real time dataset using Rapidminer. The Analysis is done on the bases of the threshold and root mean square error values obtained. We are proposing the methodology which is highly competent and accurate in obtaining the results.