Numerical Modeling
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SNUPS (Simulator for Numerical P Systems) v.1.3.0.2
SNUPS (Simulator for Numerical P Systems) offer users a simulator for numerical P systems.Requirements: *
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Eclipse XML Meta-Modeling Tools v.0.0.1
The Eclipse XML Meta-Modeling Tools project provides tools like editors, extended validation and generators for developing xml based meta-models and domain-specific languages in eclipse.
Generic Eclipse Modeling System v.1.0
The Generic Eclipse Modeling System is an MDD tool for Eclipse that allows for the rapid development of GEF modeling plugins.
Java Modeling Language (JML) v.1.0
The Java Modeling Language (JML) is a behavioral interface specification language that can be used to specify the behavior of Java modules (as in design by contract -- DBC).
JPhysChem modeling tool v.1.0
JPhysChem - a mathematical modeling toolbox designed to provide an abstract layer and a comprehensive graphical front-end for general model building and specific modeling and data processing in the field of mass spectrometry and physical chemistry.
Numerical Gecko Eclipse Plugin v.1.2.0
A plugin for the Eclipse IDE implementing NumericalChameleon: a powerful numerical convertor, supporting more than 2300 units in 78 categories (physics, radixes, exchange rates, unicode, etc).
Object-Role Modeling v.1.0
The Object-Role Modeling (ORM) standard version 2, associated schemas and generation tools, and a reference implementation in the form of the Natural Object-Role Modeling Architect for Visual Studio (NORMA) product.
PySlice, parametric modeling controller v.1.6.4
Pyslice provides utility functions for parametric modeling.
MeshMagic 3D Modeling Software Free v.1.10
With MeshMagic 3D, viewing and editing stl files has never been easier. Import STL files created with CAD and drafting software. You can then use MeshMagic to rotate and rescale the existing meshes.
Numerical Plotter v.1.0
This source code enables you to plot the solutions to scientific and engineering problems.
Java Neural Modeling Framework new GUI v.1.0
Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.