This paper evaluates the potential of different artificial neural network models for classifying Internet users based on their hourly traffic profile. The ...
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This paper evaluates the potential of different artificial Neural Network models for classifying Internet users based on their hourly traffic profile.
This paper evaluates the potential of different artificial Neural. Network models for classifying Internet users based on their hourly traffic profile. The ...
In this paper we compare the use of discriminant analysis and artificial neural networks for the classification of Internet users. The classification is based ...
In this paper we use supervised machine learning within a neural network to develop a model capable of achieving high classification accuracy and maintaining ...
This paper evaluates the potential of different artificial neural network models for classifying Internet users based on their hourly traffic profile. The ...
This study aims to classify bloggers in the Kohkiloye and Boyer Ahmad Province in Iran where causes of users tend cyberspace on there. The database was got from.
In this paper we compare the use of Discriminant Analysis and artificial Neural Networks for the classification of Internet users. The classification is based ...
Using Neural Networks to Classify Internet Users | Proceedings of ...
dl.acm.org › doi › AICT.2005.93
This paper evaluates the potential of different artificial Neural Network models for classifying Internet users based on their hourly traffic profile. The ...
Aug 29, 2024 · The authors of presented a K-NN approach which achieved a 99.4% accuracy in classifying DNS, Telnet, Ping, and Voice traffic with real-time data ...