Search Results for "x-art"

GatcomSUMO is a multi-platform application that facilitates the building of VANET simulations using the SUMO traffic simulator and the OMNeT++ network simulator. The tasks related to the generation of abstract or synthetic scenarios, the download and conversion of network scenarios based on real maps (e.g. from OpenStreetMap), the route creation process, and the vehicles mobility modelling are integrated in a user-friendly graphical interface. This tool performs the necessary actions by...

The Common Open Research Emulator (CORE) is a tool for emulating networks on one or more machines. You can connect these emulated networks to live networks. CORE consists of a GUI for drawing topologies of lightweight virtual machines, and Python modules for scripting network emulation.

tlearn is a backpropagation neural network simulator, written by Jeff Elman. xtlearn is a version of tlearn for the X Window System. OSXtlearn is xtlearn wrapped in a MacOSX application bundle that runs ons MacOSX 10.5 or higher and that requires XQuartz. OSXtlearn is created by Harm Brouwer.

...evoTopo can be used with any wireless network simulator that will accept a node position file of some form. The reference file must be given in .csv format listing the x- and y-coordinates of the nodes. evoTopo is written in Java and will run on Java 6 or higher. It is released under the GPL v3 license. It comes with reference topology files in .csv format for mesh networks deployed in Berlin, Wien, Leipzig and MIT. See the README file for further information.

Simured is a multicomputer network simulation whith visual interface to see packet movement on the network. It is multi platform and there are versions in Java and C++.

This is a application for simula Neuronals Networks, now only support the Backpropagation Network. In the future maybe support ART, Adaline, Madaline, and other Neuronal Networks. Use gnuplot to draw the lms error.

GNNS - GNNS Neural Network Simulator, is both a set of libraries and an interface for creating and learning neural networks. It is aimed to support as many network typs and learning algorithms as possible. GNNS is meant to support different platforms.