The NeuroGenetic Optimizer automates neural network design and training by searching through combinations of input variables, neural model architectures and also their internal structures to evolve committees of fully trained high performance robust models that predict what you seek. It is particularly good at time-series modeling.
References in zbMATH (referenced in 1 article )
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- Rummler, Andreas; Scarbata, Gerd: eaLib -- a Java framework for implementation of evolutionary algorithms (2001)