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FREVO is an open-source framework developed in Java to help engineers and scientists in evolutionary design or optimization tasks. The major feature of FREVO is the componentwise decomposition and separation of the key building blocks for each optimization tasks. We identify these as the problem definition, solution representation and the optimization method. This structure enables the components to be designed separately allowing the user to easily swap and evaluate different configurations and methods or to connect an external simulation tool. The latest version in development is hosted at https://github.com/smartgrids-aau/Frevo

Java Interface for Neural and Genetic Pattern Classification JINGPaC is a framework to solve the problem of Pattern Classification thanks to Genetic Programming, Neural Network, Genetic Algorithms and many other techniques. JINGPaC2 is the latest version

Lightweight backpropagation neural network in C++. The project provides a class implementing a feedforward neural network, and a class for easily train it. It is highly customizable to manage your problem and comes with a simple graphical interface.