SwingNN 3.0
Publisher's Description
Y
our data is imported into a grid and used to train a neural network. The input values are forced to swing beyond their limits. The output values are forecasted by the neural network. A new neural network is created using the new inputs and forecasted outputs. The neural networks are compared. The inputs are adjusted and another new neural network is created. The process continues until a new neural network agrees with the original about the forecasts. The forecasts are added to the grid for you to use.
Requirements
4 MBytes HD
Changes: 3.0
Bug fixes and performance improvements
Languages supported
English
