We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Recently, there are many researchers to design Bayesian network structures using evolutionary algorithms but most of them use the only one fittest solution in the last generation. ...
Two distinct learning mechanisms are considered for a population of agents who engage in decentralized search for the common optimum. An agent may choose to learn via innovation (...
Firewalls provide very good network security features. However, classical perimeter firewall deployments suffer from limitations due to complex network topologies and the inabilit...
The necessity of network traffic monitoring and analysis is growing dramatically with increasing network usage demands from individual users as well as business communities. Most ...