VisSim/NeuralNet
Introduction
VisSim/NeuralNet excels at nonlinear system identification, problem diagnosis, decision making, prediction, and other problems where pattern recognition is important and precise computational answers are not readily available.
Within the engineering community, scientists are using neural networks for learning nonlinear dynamic behavior from historic data sets. Once trained, neural networks are used to predict plant behavior based on input values. Neural networks can be both trained and used for prediction directly from a VisSim diagram.
Features
Five learning methods
- Continuous and discrete outputs
- Supports definition of network topology, learning coefficients, and methods
- Interactive modification of training characteristics and learning methods
- Monitor learning error interactively
- Save and restore learned weights