Neuronet modelling of indicators of quality of process carbonization

Abstract

In the given work the expediency of modelling of indicators of quality of process carbonization the ammoniated brine on the basis of use of artificial neural networks was investigated. On experimental data factors of communications between neurons networks which realise dependence between the entrance data for a network (parametres of raw streams are found: temperature, the expense, pressure etc.) and the target data (indicators of quality of process carbonization).