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Volumn 47, Issue 1, 2007, Pages 67-72

Prediction of iron ore pellet strength using artificial neural network model

Author keywords

Basicity; Bentonite; Burn through temperature; CCS; Green pellet; Induration; Neural network; Pellet quality; Pelletization

Indexed keywords

ALKALINITY; BENTONITE; BLAST FURNACES; COMPACTION; NEURAL NETWORKS; STRENGTH OF MATERIALS;

EID: 34247180596     PISSN: 09151559     EISSN: None     Source Type: Journal    
DOI: 10.2355/isijinternational.47.67     Document Type: Article
Times cited : (38)

References (13)
  • 8
    • 34247259369 scopus 로고    scopus 로고
    • V. Niiniskorpi: ISS Tech. 2003 Conf. Proc., Iron and Steel Society, Warrendale, PA (USA), (2003), 71.
    • V. Niiniskorpi: ISS Tech. 2003 Conf. Proc., Iron and Steel Society, Warrendale, PA (USA), (2003), 71.
  • 10
    • 0043202583 scopus 로고    scopus 로고
    • Iron and Steel Society, Warrendale, PA USA
    • V. Niiniskorpi: 61st Iron Making Conf. Proc., Iron and Steel Society, Warrendale, PA (USA), (2002), 533.
    • (2002) 61st Iron Making Conf. Proc , pp. 533
    • Niiniskorpi, V.1
  • 11
    • 0004247903 scopus 로고
    • Springer-Verlag, Berlin, Heidelberg
    • K. Mayer: Pelletizing of Iron Ore, Springer-Verlag, Berlin, Heidelberg, (1980), 265.
    • (1980) Pelletizing of Iron Ore , pp. 265
    • Mayer, K.1
  • 13
    • 0344493982 scopus 로고    scopus 로고
    • C. E. Loo and W. Leung: ISIJ Int., 43 (2003), No. 9, 1395.
    • (2003) ISIJ Int , vol.43 , Issue.9 , pp. 1395
    • Loo, C.E.1    Leung, W.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.