Now we combine PR-DDNN with separation of the interaction potential from the lowdimensional potential with the SBW parametrically managed activation function for semiautomatic simultaneous diabatization and adiabatic surface fitting. We will call the neural network that combines these features a parametrically managed DDNN or PM-DDNN. The PM-DDNN forces the global potential energy surfaces to behave as low-dimensional potentials at dissociation-limit geometries.