A COMPARATIVE STUDY FOR WEB SERVICES RESPONSE TIME PREDICTION
A COMPARATIVE STUDY FOR WEB SERVICES RESPONSE TIME PREDICTION

Summary/Abstract: Web-based learning communities could significantly benefit from having as feature adaptive systems. Those models take advantage of the knowledge and experiences of community affiliates and utilize it to better serve each person. Recurrent neural networks have proven their predictive capability on time series. In this study, we compare the prediction accuracy of three recurrent networks on a data set that consists of real world web services response time. We also have investigated the effect of encoded inputs on the prediction accuracy of the three models.

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