메뉴 건너뛰기




Volumn 5, Issue , 2003, Pages 4451-4456

A new annealing robust fuzzy basis function for modeling with outliers

Author keywords

Annealing robust fuzzy basis function; Annealing robust learning algorithm; Outliers; Repeated support vector regression

Indexed keywords

FUNCTION EVALUATION; FUZZY SETS; LEARNING ALGORITHMS; MATHEMATICAL MODELS; PARAMETER ESTIMATION; PROBLEM SOLVING; REGRESSION ANALYSIS; VECTOR QUANTIZATION;

EID: 0242721256     PISSN: 08843627     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (13)
  • 1
    • 0028428006 scopus 로고
    • A robust back-propagation learning algorithm for function approximation
    • May
    • D. S. Chen and R. C. Jain, "A robust back-propagation learning algorithm for function approximation," IEEE Trans. Neural Networks, vol. 5, no. 3, May, pp. 467-479, 1994.
    • (1994) IEEE Trans. Neural Networks , vol.5 , Issue.3 , pp. 467-479
    • Chen, D.S.1    Jain, R.C.2
  • 2
    • 0034271492 scopus 로고    scopus 로고
    • The annealing robust backpropagation (BP) learning algorithm
    • C. C. Chuang, S. F. Su and C. C. Hsiao, "The Annealing Robust Backpropagation (BP) Learning Algorithm," IEEE Trans. Neural Networks, vol. 11, no. 5, pp. 1067-1077, 2000.
    • (2000) IEEE Trans. Neural Networks , vol.11 , Issue.5 , pp. 1067-1077
    • Chuang, C.C.1    Su, S.F.2    Hsiao, C.C.3
  • 5
    • 0029777584 scopus 로고    scopus 로고
    • Robust error measure for supervised neural network learning with outliers
    • January
    • K. Liano, "Robust error measure for supervised neural network learning with outliers," IEEE Trans. Neural Networks, vol. 7, no. 1, January, pp. 246-250, 1996.
    • (1996) IEEE Trans. Neural Networks , vol.7 , Issue.1 , pp. 246-250
    • Liano, K.1
  • 7
    • 0029156915 scopus 로고
    • Robustization of learning method for RBF networks
    • V. David Sanchez, "Robustization of learning method for RBF networks," Neurocomputing vol. 9, pp. 85-94, 1995.
    • (1995) Neurocomputing , vol.9 , pp. 85-94
    • Sanchez, V.D.1
  • 8
    • 0031272926 scopus 로고    scopus 로고
    • Comparing support vector machines with Gaussian kernels to radial basis function classifiers
    • B. Schölkopf, et al. "Comparing support vector machines with Gaussian kernels to radial basis function classifiers," IEEE Transactions on Signal Processing, Vol. 45, No. 11, pp. 2758-2765, 1997.
    • (1997) IEEE Transactions on Signal Processing , vol.45 , Issue.11 , pp. 2758-2765
    • Schölkopf, B.1
  • 9
    • 24044515976 scopus 로고    scopus 로고
    • On a kernel-based method for pattern recognition, regression, approximation and operator inversion
    • A. J. Smola and B. Schölkopf, "On a kernel-based method for pattern recognition, regression, approximation and operator inversion," Algorithmica, 1998. Also available from URL: http://svm.first.gmd.de/papers.html.
    • (1998) Algorithmica
    • Smola, A.J.1    Schölkopf, B.2
  • 10
    • 0003401675 scopus 로고    scopus 로고
    • A tutorial on support vector regression
    • Neuro COLT Technical Report TR-1998-030, Royal Holloway College
    • J. Smola and B. Schölkopf, A Tutorial on Support Vector Regression, Neuro COLT Technical Report TR-1998-030, Royal Holloway College, 1998.
    • (1998)
    • Smola, J.1    Schölkopf, B.2
  • 13
    • 84887252594 scopus 로고    scopus 로고
    • Support vector method for function approximation, regression estimation, and signal processing
    • V. Vapnik, S. Golowich and A. J. Smola, "Support vector method for function approximation, regression estimation, and signal processing," Neural Information Processing Systems, 9, 1997.
    • (1997) Neural Information Processing Systems , vol.9
    • Vapnik, V.1    Golowich, S.2    Smola, A.J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.