메뉴 건너뛰기




Volumn 34, Issue 2, 2012, Pages 217-221

Development of a model selection method based on the reliability of a soft sensor model

Author keywords

Model selection; Moving window; Process control; Soft sensor; Time difference

Indexed keywords


EID: 84861955990     PISSN: 01253395     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (9)

References (11)
  • 2
    • 0028416938 scopus 로고
    • Independent component analysis, A new concept?
    • Comon, P. 1994. Independent component analysis, A new concept? Signal Processing. 36, 287-314.
    • (1994) Signal Processing , vol.36 , pp. 287-314
    • Comon, P.1
  • 7
    • 79959784751 scopus 로고    scopus 로고
    • Maintenance-Free Soft Sensor Models with Time Difference of Process Variables
    • Kaneko, H. and Funatsu, K. 2011. Maintenance-Free Soft Sensor Models with Time Difference of Process Variables. Chemometrics and Intelligent Laboratory Systems. 107, 312-317.
    • (2011) Chemometrics and Intelligent Laboratory Systems , vol.107 , pp. 312-317
    • Kaneko, H.1    Funatsu, K.2
  • 8
    • 80055094175 scopus 로고    scopus 로고
    • A Soft Sensor Method Based on Values Predicted from Multiple Intervals of Time Difference for Improvement and Estimation of Prediction Accuracy
    • Kaneko, H. and Funatsu, K. 2011. A Soft Sensor Method Based on Values Predicted from Multiple Intervals of Time Difference for Improvement and Estimation of Prediction Accuracy. Chemometrics and Intelligent Laboratory Systems. 109, 197-206.
    • (2011) Chemometrics and Intelligent Laboratory Systems , vol.109 , pp. 197-206
    • Kaneko, H.1    Funatsu, K.2
  • 9
    • 35548968908 scopus 로고    scopus 로고
    • Data-based process monitoring, process control and quality improvement: Recent developments and applications in steel industry
    • Kano, M. and Nakagawa, Y. 2008. Data-based process monitoring, process control and quality improvement: Recent developments and applications in steel industry. Computers and Chemical Engineering. 32, 12-24.
    • (2008) Computers and Chemical Engineering , vol.32 , pp. 12-24
    • Kano, M.1    Nakagawa, Y.2
  • 10
    • 18844397336 scopus 로고    scopus 로고
    • Application of latent variable methods to process control and multivariate statistical process control in industry
    • Kourti, T. 2005. Application of latent variable methods to process control and multivariate statistical process control in industry. Adaptive Control and Signal Processing. 19, 213-246.
    • (2005) Adaptive Control and Signal Processing , vol.19 , pp. 213-246
    • Kourti, T.1
  • 11
    • 0032044750 scopus 로고    scopus 로고
    • Recursive PLS algorithms for adaptive data modeling
    • Qin, S.J. 1998. Recursive PLS algorithms for adaptive data modeling. Computers and Chemical Engineering. 22, 503-514.
    • (1998) Computers and Chemical Engineering , vol.22 , pp. 503-514
    • Qin, S.J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.