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Volumn 39, Issue 7, 2000, Pages 2355-2367

Using mixture principal component analysis networks to extract fuzzy rules from data

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; EXPERT SYSTEMS; FAILURE ANALYSIS; GENETIC ALGORITHMS; HEURISTIC METHODS; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; MAXIMUM LIKELIHOOD ESTIMATION; MEMBERSHIP FUNCTIONS; NEURAL NETWORKS;

EID: 0034235548     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie9905613     Document Type: Article
Times cited : (18)

References (35)
  • 1
    • 40649117083 scopus 로고
    • Production rules as a representation for a knowledge-based consultation program
    • Davis, R.; Buchanan, B. G.; Shortliffe, E. H. Production Rules as a Representation for a Knowledge-Based Consultation Program. Art. Intell. 1977, 8, 15.
    • (1977) Art. Intell. , vol.8 , pp. 15
    • Davis, R.1    Buchanan, B.G.2    Shortliffe, E.H.3
  • 3
    • 0024685622 scopus 로고
    • BIOEXPERT - An expert system for wastewater treatment process diagnosis
    • Lapointe, J.; Marcos, B.; Veillette, M.; Laflamme, G. BIOEXPERT - An Expert System for Wastewater Treatment Process Diagnosis. Comput. Chem. Eng. 1989, 13, 619.
    • (1989) Comput. Chem. Eng. , vol.13 , pp. 619
    • Lapointe, J.1    Marcos, B.2    Veillette, M.3    Laflamme, G.4
  • 4
    • 85037965633 scopus 로고
    • CATDEX: An expert system for diagnosing a fluidized catalytic cracking unit
    • CACHE Case Study Series; CACHE Corp.: Austin, TX
    • Venkatasubramanian, V. CATDEX: An Expert System for Diagnosing a Fluidized Catalytic Cracking Unit. In Knowledge-Based System in Chemical Engineering; CACHE Case Study Series; CACHE Corp.: Austin, TX, 1988; Vol. 1.
    • (1988) Knowledge-Based System in Chemical Engineering , vol.1
    • Venkatasubramanian, V.1
  • 6
    • 0008531564 scopus 로고
    • Expert systems and connectionist networks
    • Rfeifer, R., Schreter, Z., Fogeelman-Soulie, F., Steels, L., Eds.; North-Holland: New York
    • Bounds, D. G. Expert Systems and Connectionist Networks. In Connectionism in Perspective; Rfeifer, R., Schreter, Z., Fogeelman-Soulie, F., Steels, L., Eds.; North-Holland: New York, 1989.
    • (1989) Connectionism in Perspective
    • Bounds, D.G.1
  • 7
    • 84920183623 scopus 로고
    • Rule learning by searching on adapted nets
    • Fu, L. M. Rule Learning by Searching on Adapted Nets. AAAI '91 1991, 590.
    • (1991) AAAI '91 , pp. 590
    • Fu, L.M.1
  • 9
    • 0030291656 scopus 로고    scopus 로고
    • Rule-based characterization of industrial flotation processes with inductive techniques and genetic algorithms
    • Gouws, F. S.; Aldrich, C. Rule-Based Characterization of Industrial Flotation Processes with Inductive Techniques and Genetic Algorithms. Ind. Eng. Chem. Res. 1996, 35, 4119.
    • (1996) Ind. Eng. Chem. Res. , vol.35 , pp. 4119
    • Gouws, F.S.1    Aldrich, C.2
  • 11
    • 0001703957 scopus 로고    scopus 로고
    • Neuro-fuzzy method to learn fuzzy classification rules from data
    • Nauck, D.; Kruse, R. A Neuro-Fuzzy Method to Learn Fuzzy Classification Rules from Data. Fuzzy Sets Syst. 1997, 89, 277.
    • (1997) Fuzzy Sets Syst. , vol.89 , pp. 277
    • Nauck, D.1    Kruse, R.A.2
  • 12
    • 0031274113 scopus 로고    scopus 로고
    • Knowledge-based fuzzy MLP for classification and rule generation
    • Mitra, S.; De, R. K.; Pal, S. K. Knowledge-Based Fuzzy MLP for Classification and Rule Generation. IEEE Trans. Neural Networks 1997, 8, 1338.
    • (1997) IEEE Trans. Neural Networks , vol.8 , pp. 1338
    • Mitra, S.1    De, R.K.2    Pal, S.K.3
  • 13
    • 0031206677 scopus 로고    scopus 로고
    • Neuro-fuzzy systems for diagnosis
    • Isermann, R.; Ayoubi, M. Neuro-Fuzzy Systems for Diagnosis. Fuzzy Sets Syst. 1997, 89, 289.
    • (1997) Fuzzy Sets Syst. , vol.89 , pp. 289
    • Isermann, R.1    Ayoubi, M.2
  • 14
    • 0026925677 scopus 로고
    • Self-learning fuzzy controller based on temporal back-propagation
    • Jang, J. S. R. Self-learning Fuzzy Controller Based on Temporal Back-Propagation. IEEE Trans. Neural Networks 1992, 3, 714.
    • (1992) IEEE Trans. Neural Networks , vol.3 , pp. 714
    • Jang, J.S.R.1
  • 15
    • 0032898793 scopus 로고    scopus 로고
    • Mixture principal component analysis models for process monitoring
    • Chen, J.; Liu, J. Mixture Principal Component Analysis Models for Process Monitoring. Ind. Eng. Chem. Res. 1999, 38, 1478.
    • (1999) Ind. Eng. Chem. Res. , vol.38 , pp. 1478
    • Chen, J.1    Liu, J.2
  • 17
    • 0026135904 scopus 로고
    • Radial basis function networks for classifying process faults
    • Leonard, J.; Kramer, M. Radial Basis Function Networks for Classifying Process Faults. IEEE Control Syst. 1991, 31.
    • (1991) IEEE Control Syst. , pp. 31
    • Leonard, J.1    Kramer, M.2
  • 18
    • 0001473437 scopus 로고
    • On estimation of probability density function and model
    • Parzen, E. On Estimation of Probability Density Function and Model. Ann. Math. Stat. 1962, 33, 1065.
    • (1962) Ann. Math. Stat. , vol.33 , pp. 1065
    • Parzen, E.1
  • 19
    • 0016973661 scopus 로고
    • Pattern recognition by means of disjoint principal components model
    • Wold, S. Pattern Recognition by Means of Disjoint Principal Components Model. Pattern Recognit. 1976, 8, 127.
    • (1976) Pattern Recognit. , vol.8 , pp. 127
    • Wold, S.1
  • 20
    • 0027543492 scopus 로고
    • Representing bounded fault classes using neural networks with ellipsoidal activation functions
    • Kavuri, S.; Venkatasubramanian, V. Representing Bounded Fault Classes Using Neural Networks with Ellipsoidal Activation Functions. Comput. Chem. Eng. 1993, 17, 139.
    • (1993) Comput. Chem. Eng. , vol.17 , pp. 139
    • Kavuri, S.1    Venkatasubramanian, V.2
  • 21
    • 0027643095 scopus 로고
    • Using fuzzy clustering with ellipsoidal units in neural networks for robust fault classification
    • Kavuri, S.; Venkatasubramanian, V. Using Fuzzy Clustering with Ellipsoidal Units in Neural Networks for Robust Fault Classification. Comput. Chem. Eng. 1993, 17, 765.
    • (1993) Comput. Chem. Eng. , vol.17 , pp. 765
    • Kavuri, S.1    Venkatasubramanian, V.2
  • 22
    • 0026374269 scopus 로고
    • Generalization accuracy of probabilistic neural networks compared with backpropagation networks
    • Specht, D. F. Generalization Accuracy of Probabilistic Neural Networks Compared with Backpropagation Networks. IJCNN-91-Seattle: Int. Joint Conf. Neural Networks 1991, 1, 887.
    • (1991) IJCNN-91-Seattle: Int. Joint Conf. Neural Networks , vol.1 , pp. 887
    • Specht, D.F.1
  • 24
    • 0025514444 scopus 로고
    • A theoretical basis for the use of principal components method for monitoring multivariate processes
    • Wise, B. M.; Ricker, N. L.; Veitkamp, D. J.; Kowalski, B. R. A Theoretical Basis for the Use of Principal Components Method for Monitoring Multivariate Processes. Process Control Qual. 1990, 1, 41.
    • (1990) Process Control Qual. , vol.1 , pp. 41
    • Wise, B.M.1    Ricker, N.L.2    Veitkamp, D.J.3    Kowalski, B.R.4
  • 25
    • 0026108818 scopus 로고
    • Multivariate statistical monitoring of process operating performance
    • Kresta, J. V.; MacGregor, J. F.; Marlin, T. E. Multivariate Statistical Monitoring of Process Operating Performance. Can, J. Chem. Eng. 1991, 69, 35.
    • (1991) Can, J. Chem. Eng. , vol.69 , pp. 35
    • Kresta, J.V.1    MacGregor, J.F.2    Marlin, T.E.3
  • 26
    • 0025234077 scopus 로고
    • Quadratic function nodes: Use, structure and training
    • Volper, D. J.; Hampson, S. E. Quadratic Function Nodes: Use, Structure and Training. Neural Networks 1990, 3, 93.
    • (1990) Neural Networks , vol.3 , pp. 93
    • Volper, D.J.1    Hampson, S.E.2
  • 27
    • 0000262562 scopus 로고
    • Hierarchical mixture of expert and the EM algorithm
    • Jordan, M. I.; Jacobs, R. A. Hierarchical Mixture of Expert and the EM Algorithm. Neural Comput. 1994, 6, 181.
    • (1994) Neural Comput. , vol.6 , pp. 181
    • Jordan, M.I.1    Jacobs, R.A.2
  • 29
    • 0028517197 scopus 로고
    • Probability density estimation using elliptical basis functions
    • Johnston, L. P. M.; Kramer, M. A. Probability Density Estimation Using Elliptical Basis Functions. AIChE J. 1994, 40, 1639.
    • (1994) AIChE J. , vol.40 , pp. 1639
    • Johnston, L.P.M.1    Kramer, M.A.2
  • 32
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EM algorithm
    • Dempster, A. P.; Laird, N. M.; Rubin, D. B. Maximum Likelihood from Incomplete Data via the EM Algorithm. J. R. Stat. Soc. Ser. B 1977, 39, 1.
    • (1977) J. R. Stat. Soc. Ser. B , vol.39 , pp. 1
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 33
    • 0000696616 scopus 로고
    • Neural networks and related methods for classification
    • Ripley, B. D. Neural Networks and Related Methods for Classification, J. R. Stat. Soc. Ser. B 1994, 56, 409.
    • (1994) J. R. Stat. Soc. Ser. B , vol.56 , pp. 409
    • Ripley, B.D.1
  • 34
    • 0024764296 scopus 로고
    • Incipient fault diagnosis of chemical processes via artificial neural networks
    • Watanabe, K.; Matsuura, I.; Abe, M.; Kubota, M.; Himmelblau, D. M. Incipient Fault Diagnosis of Chemical Processes via Artificial Neural Networks. AIChE J. 1989, 35, 1803.
    • (1989) AIChE J. , vol.35 , pp. 1803
    • Watanabe, K.1    Matsuura, I.2    Abe, M.3    Kubota, M.4    Himmelblau, D.M.5
  • 35
    • 0027333737 scopus 로고
    • An approach to fault diagnosis of chemical processes via neural networks
    • Fan, J. Y.; Nikolaou, M.; White, R. E. An Approach to Fault Diagnosis of Chemical Processes via Neural Networks. AIChE J. 1993, 39, 82.
    • (1993) AIChE J. , vol.39 , pp. 82
    • Fan, J.Y.1    Nikolaou, M.2    White, R.E.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.