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Volumn 51, Issue 2, 2002, Pages 217-226

A probabilistic neural network approach for modeling and classification of bacterial growth/no-growth data

Author keywords

Bacterial growth; Logistic regression; Modeling; Probabilistic neural networks

Indexed keywords

WATER;

EID: 0036064637     PISSN: 01677012     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-7012(02)00080-5     Document Type: Article
Times cited : (115)

References (24)
  • 12
    • 0034946875 scopus 로고    scopus 로고
    • Application of artificial neural networks for predicting the thermal inactivation of bacteria: A combined effect of temperature, pH, and water activity
    • (2001) Food Research International , vol.34 , pp. 573-579
    • Lou, W.1    Nakai, S.2
  • 21
    • 0035139570 scopus 로고    scopus 로고
    • Probabilistic neural networks using Bayesian decision strategies and a modified Gompertz model for growth phase classification in the batch culture of Bacillus subtilis
    • (2001) Biochemical Engineering Journal , vol.7 , Issue.1 , pp. 41-48
    • Simon, L.1    Karim, M.N.2
  • 24
    • 0030297904 scopus 로고    scopus 로고
    • Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes
    • (2000) Journal of Clinical Epidemiology , vol.49 , Issue.11 , pp. 1225-1231
    • Tu, J.V.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.