Search Results for "algorithm" - Page 3
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Showing 69 open source projects for "algorithm"
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This project implements an algorithm for segmenting protein sequences into smaller meaningful blocks. The method is based on the pure statistical approach and it uses an analogy between proteins and natural language.
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PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.
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Processes boolean functions which can be provided either as a list of 0s and 1s or which can be provided as a formula in first-order logic (using disjunctive or conjunctive normal forms). Internally the Quine McCluskey algorithm is used.
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The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
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PyLife is an implementation of the game of life algorithm featuring parallel programming. It uses MPI and python to achieve a consistent software architecture and reliably performance.
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DrPangloss is a python implementation of a three operator genetic algorithm, complete with a java swing GUI for running the GA and visualising performance, generation by generation
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PyPotrace is a Python programming language binding for Peter Selinger's Potrace raster to vector conversion algorithm. No separate Potrace library or application required!
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A Python and ANSI C implementation of the Edelsbrunner hyperplane arrangement algorithm described in his book Algorithms in Combinatorial Geometry, supporting arbitrary dimensions, exact rational arithmetic using gmp, and using David Avis lrs solver.
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KU1K is a set of tools for 4D,5D and 6D compact U(1) lattice gauge theory Monte Carlo simulation using the Skipis-Vantzos algorithm. As the calculations involved, even for the 4D case, are consuming, the project is modular so as to run on the Grid.
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Galileo is a library for developing custom distributed genetic algorithms developed in Python. It provides a robust set of objects that can be used directly or as the basis of derived objects. Its modularity makes it easy to extend the functionality. The
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Python Trust Metrics. Implementation of Ford-Faulkersson Maximum Flow algorithm and mod_virgule's Trust Metrics code, in python
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A Genetic Algorithm Training System in Python. Gatspy provides the framework, the user provides the error (fitness) function. Gatspy will evolve a solution that attempts to minimize the error.
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aVolve is an evolutionary/genetic algorithm designed to evolve single-cell organisms in a micro ecosystem. It currently uses the JGAP Genetic algorithm, but does include a primitive genetic algorithm written in Python.
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nBoost is a suite of boosting algorithms designed to solve binary classification problems on data that is not linearly separable by a convex combination of base hypotheses, i.e. noisy data. WARNING: Active development. Underlying algorithm is unstable.
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devsimpy
Python-based GUI for discrete-event system modeling and simulation
DEVSimPy is an advanced wxPython GUI for the modeling and simulation of systems based on the DEVS (Discrete EVent system Specification) formalism. Features include powerful built-in editor, advanced modeling approach, powerful discrete event simulation algorithm, import/export DEVS components library and more.
