Obiettivo The project objective is to improve end-point analysis and temperature control in the BOS process through the application of neural networks to current computer models for primary charge balancing, sub-lance end-blow control and end-point analysis prediction. Conventional statistical process models based on thermal or physical logic are limited in their ability to account for interrelated variables whose influence is not well understood. Neural networks with their self-learning capabilities are expected to be more accurate, faster and more precise. Programma(i) ECSC-STEEL C - Medium-term guidelines for the ECSC steel RTD programme of research and pilot/demonstration projects, 1996-2002 Argomento(i) C1 - Primary steelmaking Invito a presentare proposte Data not available Meccanismo di finanziamento CSC - Cost-sharing contracts Coordinatore British Steel plc Contributo UE Nessun dato Indirizzo Moorgate S60 3AR Rotherham Regno Unito Mostra sulla mappa Costo totale Nessun dato Partecipanti (2) Classifica in ordine alfabetico Classifica per Contributo UE Espandi tutto Riduci tutto INSTITUT FÜR BERGWERKS- UND HÜTTENMASCHINENKUNDE DER RWTH AACHEN Germania Contributo UE Nessun dato Indirizzo Wüllnerstrasse, 2 52056 AACHEN Mostra sulla mappa Costo totale Nessun dato KONINKLIJKE HOOGOVENS Paesi Bassi Contributo UE Nessun dato Indirizzo 1970 CA IJMUIDEN Mostra sulla mappa Costo totale Nessun dato