JETNET 3.0 is initialized by calling the subroutine JNINIT. It allows for switching between different learning rates at convenience during execution, but each learning algorithm uses specific parameters that need to be initialized. The default values of these parameters give good results in most cases.
The ANN architecture (number of hidden layers, nodes, etc.) is designed through the switches MSTJN(1) and MSTJN(10-19). The distribution of the initial weights is set by the parameter PARJN(4). Naturally, these switches and parameters must be set prior to calling JNINIT.