Open AccessModified chaotic adding weight one_rank local_region forecasting for silicon content in molten iron of blast furnace
Author(s) -
Chuanhou Gao,
Zhimin Zhou
Publication year - 2004
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.53.4092
Subject(s) - blast furnace , silicon , weighting , chaotic , matrix (chemical analysis) , materials science , rank (graph theory) , content (measure theory) , entropy (arrow of time) , computer science , metallurgy , mathematics , thermodynamics , composite material , physics , artificial intelligence , mathematical analysis , combinatorics , acoustics
Based on the usual chaotic-weighting first-rank local-region forecas ting model, a modification is made for the predictor in matrix and vector simulation instead of single variant. Then the modified forec asting model is applied to pr edict silicon content in molten iron of the medium-sized blast furnace in China, and good results are obtained. Finally, we find that the value of Kolmogo rov entropy has a great effect on the hitting accuracy of the prediction .