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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.
JGAP is a Genetic Algorithms and Genetic Programming package written in Java. It is designed to require minimum effort to use, but is also designed to be highly modular. JGAP features grid functionality and a lot of examples. Many unit tests included.
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Darwin 2: Java Framework for Evolutionary Computation (geneticalgorithm, GA). A true framework with out-of-the-box functionality and extensibility of all classes. Interface-based pattern with dependency-injection to configure components.
OpenForecast is a package of general purpose, forecasting models written in Java that can be applied to any data series. No knowledge of forecasting is required. Using this package, the most appropriate algorithm for your data will be selected.
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Optex Analyzer is a software to analyze and compare algorithms to solve approximately optimization problems. It has a GUI that allows select a set of input files containing raw algorithm results. The analysis is shown with tables and charts.
This project intends to create an indexing search engine, for knowledge management. The primary object is to apply an information retrieval core. And implement a knowledge data discovery theory such as data mining algorithm, text mining.
This project provides a JAVA library and a graphical user interface which implement the "FastICA" algorithm based on the paper "Fast and Robust Fixed-Point Algorithms for Independent Component Analysis (ICA)" by Aapo Hyvärinen.
Java Randomness Test Suite is a gui application to run randomness tests on random stream resource (file or algorithm). Application can be run in command line. Includes general statistical tests, NIST and DIEHARD tests.
VKAS uses genetic programming methods to find out the relationship among a set of independent and dependent variable. It is a problem solver software which uses evolutionary computing methods.
When vkas is run, it creates a population of chromosomes at random. This population is then genetically modified and next population is generated. Each population is subjected to fitness calculation and if a suitable answer chromosome is found then vkas stops and the answer is printed. ...
Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (geneticalgorithm) wrappers for feature selection. WEKA 3 interfaces are in development.