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NEW OPTIMIZATION TECHNOLOGY & PLANNING EXPERIMENT. Technology is designed for multidimensional optimization practical problems with continuous object functions. Technology higher efficiency than traditional optimization methods.
X-GAT (XML-based Genetic Algorithm Toolkit) is a Java framework to optimize problems with Genetic Algorithms (GAs). Differently from other frameworks, X-GAT contains ready-to-use GAs implementations and new features can be easily added.
Geneur is an Open Source scheduler for GRID. It is based on variation of genetic algorithms. Geneur uses backfill scheduling algorithm to create first genetic population.
The C++ library Geneva allows to run large scale parametric optimization problems. It can run in serial or multi-threaded mode or in a networked environment. The library currently covers Evolutionary Strategies, Genetic Algorithms and mixed scenarios.
For each Date/Time since 1582-Oct-15 (start Gregorian Calendar): ++ add/sub days&hh:mm:ss - considered all leap years; summer time DST ++ compute start/end of DST ++ compute UTC (Greenwich) to local/DST ++ weekdays ++ Excel compatible date value
PHPNN Is an open source, GPL licensed, PHP class library for the easy creation and manipulation of Neural Network based artificial intelligence. This library is intended for use in experimentation, games, quality control, or any other purpose.
A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.