This program is for constructing and training an artificial neural network with arbitrary input/output data sets. To effectively simulate the system, all key parameters of the system must be included as input or output of the neural network constructed for training. This program was written for DOS but can be run under WinXP. To run it under Windows Vista or higher, a DOS-emulator like DOSBox is required. Some of the useful features of the program are listed below:

• The size of the network that can be constructed is only limited by DOS memory.
• Different training algorithms are available, e.g., steepest descent, conjugate gradient, DFP, BFGS and Maquardt-Levenberg.
• A heuristic search algorithm, partially based on quadratic interpolation, has been used to find out optimum step size for each iteration. This algorithm increased the training speed and accuracy many times.
• Different mode of training can be selected, e.g., pattern, moving window and block mode of training.
• Input and output data to the net can be scaled automatically. So one can instantly compare and verify the trained net for the test data set.
• Various intermediate results during training can be stored in the data files to facilitate statistical analysis.

This program can be run interactively, or in non-interactive mode by giving configuration file name as a command-line parameter. All the data files used by the program are formatted as a text file, so externally created data file may be used, but the format should be the same.

This program may be used freely for non-commercial and educational purposes. For commercial use, please contact us.