%0 Generic
%A Colla, Valentina
%A Vannucci, Marco
%A Matarese, Nicola
%A Stephens, Gerard
%A Pianezzola, Marco
%A Alonso, Izaskun
%A Lamp, Torsten
%A Palacios, Juan
%A Schiewe, Siegfried
%T Detection of transients in steel casting through standard and AI-based techniques
%J Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
%D 2011
%@ 0302-9743
%U https://hdl.handle.net/11556/2164
%X The detection of transients in the practice of continuous casting within a steel-making industry is a key task for the prediction of final product properties but currently a direct observation of this phenomenon is not available. For this reason in this paper several standard and soft-computing based methods for the detection of transients from plant data will be tested and compared. From the obtained results it emerges that the use of a fuzzy inference system based on experts knowledge achieves very satisfactory results correctly identifying most of the transient events present in the databases provided by different companies.
%~