Neural-network-based forecating model for controlof silver biosorption processes

We study the specific features of control in course of silver biosorption from biosorbents – secondary solutions originated from pharmaceutical industry production wastes. The plant state fore-casting model is implemented with a multi-layer multi-input neural network with inter-layer routing logic induced by logic of process-ing units switching. Existence of Koshi boundary conditions is assured at every switch point.