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Volumn 26, Issue 11, 2005, Pages 1025-1028

Soft sensing modeling based on support vector machines for fermentation process

Author keywords

Fermentation process; Least square support vector machine; Modeling; Penicillin concentration; Soft sensing

Indexed keywords

COMPUTER SIMULATION; CONDITION MONITORING; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; MEDICINE; ONLINE SYSTEMS; QUALITY CONTROL; REAL TIME SYSTEMS;

EID: 29144455945     PISSN: 10053026     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (4)

References (10)
  • 1
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    • Output estimation using multiple secondary measurements: High-purity distillation
    • Mejdell T, Skogestad S. Output estimation using multiple secondary measurements: high-purity distillation[J]. Process Systems Engineering, 1993, 9(10): 1641-1653.
    • (1993) Process Systems Engineering , vol.9 , Issue.10 , pp. 1641-1653
    • Mejdell, T.1    Skogestad, S.2
  • 3
    • 2342509093 scopus 로고    scopus 로고
    • PCA-DRBFN model in application to estimating dry point of pure benzene in rectifying tower
    • Chang Y Q, Wang X G, Wang F L. PCA-DRBFN model in application to estimating dry point of pure benzene in rectifying tower[J]. Journal of Northeastern University (Natural Science), 2004, 25(2): 103-105.
    • (2004) Journal of Northeastern University (Natural Science) , vol.25 , Issue.2 , pp. 103-105
    • Chang, Y.Q.1    Wang, X.G.2    Wang, F.L.3
  • 4
    • 34249753618 scopus 로고
    • Support-vector networks
    • Cortes C, Vapnik V. Support-vector networks[J]. Machine Learning, 1995, 20(1): 273-297.
    • (1995) Machine Learning , vol.20 , Issue.1 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 6
    • 0002343859 scopus 로고    scopus 로고
    • Statistical learning theory and support vector machine
    • Zhang X G. Statistical learning theory and support vector machine[J]. Journal of Automation, 2000, 26(1): 32-42.
    • (2000) Journal of Automation , vol.26 , Issue.1 , pp. 32-42
    • Zhang, X.G.1
  • 7
    • 2342567014 scopus 로고    scopus 로고
    • Soft sensing modeling based on support vector machine and Bayesian model selection
    • Yan W W, Shao H H, Wang X F. Soft sensing modeling based on support vector machine and Bayesian model selection[J]. Computers and Chemical Engineering, 2004, 28(10): 1489-1498.
    • (2004) Computers and Chemical Engineering , vol.28 , Issue.10 , pp. 1489-1498
    • Yan, W.W.1    Shao, H.H.2    Wang, X.F.3
  • 8
    • 29144497710 scopus 로고    scopus 로고
    • Soft sensor modeling based on support vector machines
    • Yan W W, Zhu H D, Shao H H. Soft sensor modeling based on support vector machines[J]. Journal of System Simulation, 2003, 15(10): 1494-1496.
    • (2003) Journal of System Simulation , vol.15 , Issue.10 , pp. 1494-1496
    • Yan, W.W.1    Zhu, H.D.2    Shao, H.H.3
  • 10
    • 0036825528 scopus 로고    scopus 로고
    • Weighted least squares support vector machines: Robustness and sparse approximation
    • Suykens J A K, Brabanter J D, Lukas L, et al. Weighted least squares support vector machines: robustness and sparse approximation[J]. Neurocomputing, 2002, 48(1): 85-105.
    • (2002) Neurocomputing , vol.48 , Issue.1 , pp. 85-105
    • Suykens, J.A.K.1    Brabanter, J.D.2    Lukas, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.