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Volumn , Issue , 2007, Pages 374-380

Neuro-fuzzy systems modeling tools for bacterial growth

Author keywords

Adaptive neurofuzzy system; Bacterial growth; Logistic regression; Multilayer perceptron; Support vector machines

Indexed keywords

DATA MINING; DATABASE SYSTEMS; FUZZY SYSTEMS; INTELLIGENT SYSTEMS; MULTILAYER NEURAL NETWORKS; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES;

EID: 36249006539     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AICCSA.2007.370908     Document Type: Conference Paper
Times cited : (4)

References (36)
  • 5
    • 0043126911 scopus 로고    scopus 로고
    • Logistic regression and artificial neural network classification models: A methodology review
    • Dreiseitla S. and Ohno-Machadob L., Logistic regression and artificial neural network classification models: a methodology review. Journal of Biomedical Informatics, 35:352-359, 2002.
    • (2002) Journal of Biomedical Informatics , vol.35 , pp. 352-359
    • Dreiseitla, S.1    Ohno-Machadob, L.2
  • 6
    • 0003922190 scopus 로고    scopus 로고
    • Wiley Interscience, Second. Edition, ISBN 0471-05669-3, John Wiley & Sons, Inc, New York
    • Duda O. R., Hart E. P., and Stork G. D., (2001), Pattern Classification, Wiley Interscience, Second. Edition, ISBN 0471-05669-3, John Wiley & Sons, Inc, New York.
    • (2001) Pattern Classification
    • Duda, O.R.1    Hart, E.P.2    Stork, G.D.3
  • 7
    • 0031127821 scopus 로고    scopus 로고
    • Fuzzy modeling and prediction of porosity and permeability from, compositional and textural attributes of sandstone
    • Fang J.H. and Chen H.C., (1997). Fuzzy modeling and prediction of porosity and permeability from, compositional and textural attributes of sandstone. Journal of Petroleum Geology, Vol. 20, No.2, pp. 185-204.
    • (1997) Journal of Petroleum Geology , vol.20 , Issue.2 , pp. 185-204
    • Fang, J.H.1    Chen, H.C.2
  • 8
    • 0001404416 scopus 로고
    • A new method of choosing the number of clusters for fuzzy c-means method
    • Japan
    • Fukuyama Y. and Sugeno M., (1989). A new method of choosing the number of clusters for fuzzy c-means method. Proceedings 5th Fuzzy System Symposium, pp. 247-250, Japan.
    • (1989) Proceedings 5th Fuzzy System Symposium , pp. 247-250
    • Fukuyama, Y.1    Sugeno, M.2
  • 10
    • 0004241258 scopus 로고    scopus 로고
    • 2nd Edition, Chapman & Hall/ CRC
    • Gordon, A. D. (1999), Classification, 2nd Edition, Chapman & Hall/ CRC.
    • (1999) Classification
    • Gordon, A.D.1
  • 12
    • 0018057468 scopus 로고
    • Fuzzy clustering with a fuzzy covariance matrix
    • IEEE Press, Piscataway, New Jersey, U.S.A, pp
    • Gustafson D. E. and Kessel W.C., (1979). Fuzzy clustering with a fuzzy covariance matrix. IEEE-CDC, Vol. 2. IEEE Press, Piscataway, New Jersey, U.S.A., pp. 761-766.
    • (1979) IEEE-CDC , vol.2 , pp. 761-766
    • Gustafson, D.E.1    Kessel, W.C.2
  • 13
    • 0037298712 scopus 로고    scopus 로고
    • Comparison of logistic regression and neural network-based classifiers for bacterial growth
    • Hajmeer M. and Basheer I., Comparison of logistic regression and neural network-based classifiers for bacterial growth. Food Microbiology, 20:43-55, 2003.
    • (2003) Food Microbiology , vol.20 , pp. 43-55
    • Hajmeer, M.1    Basheer, I.2
  • 15
    • 0035254822 scopus 로고    scopus 로고
    • An integrated neural-fuzzy-genetic-algorithm using hyper-surface membership functions to predict permeability in petroleum reservoirs
    • Huang Y., Gedeon T. D., and Wong P. M., (2001). An integrated neural-fuzzy-genetic-algorithm using hyper-surface membership functions to predict permeability in petroleum reservoirs. Engineering Applications of Artificial Intelligence, Vol. 14, No. 1, pp. 15-21.
    • (2001) Engineering Applications of Artificial Intelligence , vol.14 , Issue.1 , pp. 15-21
    • Huang, Y.1    Gedeon, T.D.2    Wong, P.M.3
  • 16
    • 1142290787 scopus 로고    scopus 로고
    • Predicting permeability from well logs in carbonates with a link to geology foe interwell permeability mapping
    • paper SPE New Orleans, Louisiana, USA
    • James J.W. and Lucia F.J., (2001). Predicting permeability from well logs in carbonates with a link to geology foe interwell permeability mapping, paper SPE (71336) presented at SPE annual technical conference New Orleans, Louisiana, USA.
    • (2001) (71336) presented at SPE annual technical conference
    • James, J.W.1    Lucia, F.J.2
  • 18
    • 0031999146 scopus 로고    scopus 로고
    • An on-line selfconstructing neural fuzzy inference network and its applications
    • Juang C. F. and Lin C.T., (1998). An on-line selfconstructing neural fuzzy inference network and its applications. IEEE Transactions Fuzzy Systems, Vol. 6, No.1, pp. 12-32.
    • (1998) IEEE Transactions Fuzzy Systems , vol.6 , Issue.1 , pp. 12-32
    • Juang, C.F.1    Lin, C.T.2
  • 20
    • 36249020171 scopus 로고    scopus 로고
    • Kandel (1992), Fuzzy expert systems. Boca Raton, Florida, U.S.A., CRC Press.
    • Kandel (1992), Fuzzy expert systems. Boca Raton, Florida, U.S.A., CRC Press.
  • 22
    • 0029236367 scopus 로고
    • Compatible cluster merging for fuzzy Modelling
    • Yokohama, Japan, pp
    • Kaymak U. and Babuska R., (1995). Compatible cluster merging for fuzzy Modelling. Proceedings, FUZZ-IEEE/IFES'95, Yokohama, Japan, pp. 897-904.
    • (1995) Proceedings, FUZZ-IEEE/IFES'95 , pp. 897-904
    • Kaymak, U.1    Babuska, R.2
  • 23
    • 34248678369 scopus 로고    scopus 로고
    • Machine learning and data mining
    • Mitchell T., Machine learning and data mining. Communications of the ACM, 4:2-11, 1999.
    • (1999) Communications of the ACM , vol.4 , pp. 2-11
    • Mitchell, T.1
  • 24
    • 0029360028 scopus 로고
    • On cluster validity for the fuzzy c-means model
    • Pal N. R. and Bezdek J.C., ( 1995). On cluster validity for the fuzzy c-means model. IEEE Trans Fuzzy Systems Vol.3, pp. 370-390.
    • (1995) IEEE Trans Fuzzy Systems , vol.3 , pp. 370-390
    • Pal, N.R.1    Bezdek, J.C.2
  • 25
    • 0141501530 scopus 로고    scopus 로고
    • Neuro-fuzzy methods for nonlinear system identification
    • Robert B. and Verbruggen H., (2003). Neuro-fuzzy methods for nonlinear system identification. Annual Reviews in Control, Vol. 27, pp.73-85.
    • (2003) Annual Reviews in Control , vol.27 , pp. 73-85
    • Robert, B.1    Verbruggen, H.2
  • 27
    • 36248958504 scopus 로고
    • Rule extraction using generalized neural networks
    • Roger J. S., (1991). Rule extraction using generalized neural networks. Proceedings SA World Congress.
    • (1991) Proceedings SA World Congress
    • Roger, J.S.1
  • 28
    • 33744584654 scopus 로고
    • Induction of decision trees
    • Quinlan J. R. (1986) "Induction of decision trees". Machine Learning, 1, 81-106.
    • (1986) Machine Learning , vol.1 , pp. 81-106
    • Quinlan, J.R.1
  • 29
    • 0034332821 scopus 로고    scopus 로고
    • Modelling the combined temperature and salt (nacl) limits for growth of a pathogenic e. coli strain using nonlinear logistic regression
    • Salter M. A., Ratkowsky D. A., Ross T., and McMeekin T A., Modelling the combined temperature and salt (nacl) limits for growth of a pathogenic e. coli strain using nonlinear logistic regression. International Journal of Food Microbiology, 61:159-167, 2000.
    • (2000) International Journal of Food Microbiology , vol.61 , pp. 159-167
    • Salter, M.A.1    Ratkowsky, D.A.2    Ross, T.3    McMeekin, T.A.4
  • 31
    • 0027544110 scopus 로고
    • A fuzzy-logic-based approach to qualitative modeling
    • Sugeno M. and Yasukawa T., (1993). A fuzzy-logic-based approach to qualitative modeling. IEEE Transactions, Fuzzy Systems, Vol. 1, pp. 7-31.
    • (1993) IEEE Transactions, Fuzzy Systems , vol.1 , pp. 7-31
    • Sugeno, M.1    Yasukawa, T.2
  • 32
    • 0021314119 scopus 로고
    • Derivation of fuzzy control rules from human operator's control actions
    • Fuzzy Information Knowledge Representation and Decision Analysis, pp
    • Takagi T. and Sugeno M., (1983). Derivation of fuzzy control rules from human operator's control actions. In Proceedings, IFAC Symposium, Fuzzy Information Knowledge Representation and Decision Analysis, pp. 55-60.
    • (1983) Proceedings, IFAC Symposium , pp. 55-60
    • Takagi, T.1    Sugeno, M.2
  • 33
    • 0021892282 scopus 로고
    • Fuzzy identification of systems and its applications to modelling and control
    • Takagi T. and Sugeno M., (1985). Fuzzy identification of systems and its applications to modelling and control. IEEE Trans Syst Man Cybernet, pp. 116-132.
    • (1985) IEEE Trans Syst Man Cybernet , pp. 116-132
    • Takagi, T.1    Sugeno, M.2
  • 34
    • 0032205732 scopus 로고    scopus 로고
    • Improving the interpretability of TSK fuzzy models by combining global learning and local learning
    • Yen J., Wang L., and Gillespie C. W., (1998). Improving the interpretability of TSK fuzzy models by combining global learning and local learning. IEEE Trans. Fuzzy Systems Vol. 6 (4), pp 531-537.
    • (1998) IEEE Trans. Fuzzy Systems , vol.6 , Issue.4 , pp. 531-537
    • Yen, J.1    Wang, L.2    Gillespie, C.W.3
  • 36
    • 0030082428 scopus 로고    scopus 로고
    • Approximation accuracy analysis of fuzzy system as function approximators
    • Zeng X. and Singh M.G., (1996). Approximation accuracy analysis of fuzzy system as function approximators. IEEE Transactions on Fuzzy Systems Vol. 4, pp. 44-63.
    • (1996) IEEE Transactions on Fuzzy Systems , vol.4 , pp. 44-63
    • Zeng, X.1    Singh, M.G.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.