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Volumn 12, Issue 2, 1996, Pages 260-272

Learning monotonic-concave interval concepts using the back-propagation neural networks

Author keywords

Concavity; Machine learning; Monotonicity; Neural networks

Indexed keywords

BACKPROPAGATION; COGNITIVE SYSTEMS; NEURAL NETWORKS;

EID: 0030148736     PISSN: 08247935     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1467-8640.1996.tb00262.x     Document Type: Article
Times cited : (3)

References (16)
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    • Adams, E.W.1    Fagot, R.F.2
  • 3
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    • Application of the back propagation neural network algorithm with monotonicity constraints for two-group classification problems
    • ARCHER, N. P., and S. WANG. 1993. Application of the back propagation neural network algorithm with monotonicity constraints for two-group classification problems. Decision Sciences, 24(1):60-75.
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    • Archer, N.P.1    Wang, S.2
  • 4
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    • Learning and classification of monotonic ordinal concepts
    • BEN-DAVID, A., L. STERLING, and Y. H. PAO. 1989. Learning and classification of monotonic ordinal concepts. Computational Intelligence, 5:45-59.
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    • Ben-David, A.1    Sterling, L.2    Pao, Y.H.3
  • 7
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    • Approximation by superpositions of a sigmoidal function
    • CYBENKO, G. 1989. Approximation by superpositions of a sigmoidal function. Mathematics of Control, Signals and Systems, 2:303-314.
    • (1989) Mathematics of Control, Signals and Systems , vol.2 , pp. 303-314
    • Cybenko, G.1
  • 9
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    • KAWABATA, T. 1991. Generalization effects of k-neighbour interpolation training. Neural Computation, 3:409-417.
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    • Kawabata, T.1
  • 11
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    • An introduction to computing with neural nets
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    • Wang, S.1
  • 16
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    • Fuzzy sets and commonsense knowledge
    • University of California, Berkeley, CA
    • ZADEH, L. 1984. Fuzzy sets and commonsense knowledge. Berkeley Cognitive Science Report No. 21, University of California, Berkeley, CA.
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    • Zadeh, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.