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Volumn 38, Issue 7, 2004, Pages 902-908

Mechanism model and artificial intelligence method for prediction and judgment of piping occurring in embankment

Author keywords

Artificial neural network; Embankment; Mechanism model; Piping

Indexed keywords

BACKPROPAGATION; DATABASE SYSTEMS; NEURAL NETWORKS; SEEPAGE; SOILS;

EID: 5744238422     PISSN: 1008973X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (9)

References (14)
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  • 2
    • 5744243931 scopus 로고    scopus 로고
    • Chinese source
  • 3
    • 5744222843 scopus 로고    scopus 로고
    • Current situation and development trend in the study of piping in the main dam of the Yangtze River
    • YANG Gui-fang, YAO Chang-hong. Current situation and development trend in the study of piping in the main dam of the Yangtze River [J]. Jiangxi Geology, 2001, 15(1): 50-52.
    • (2001) Jiangxi Geology , vol.15 , Issue.1 , pp. 50-52
    • Yang, G.-F.1    Yao, C.-H.2
  • 5
    • 0024137490 scopus 로고
    • Increased rate of convergence through learning rate adaptation
    • JACOB R A. Increased rate of convergence through learning rate adaptation [J]. Neural Networks, 1988, 1: 295-308.
    • (1988) Neural Networks , vol.1 , pp. 295-308
    • Jacob, R.A.1
  • 6
    • 5744229867 scopus 로고    scopus 로고
    • Chinese source
  • 7
    • 5744243930 scopus 로고    scopus 로고
    • Chinese source
  • 9
    • 0003407294 scopus 로고
    • A direct adaptive method for faster backpropagation learning: The RPROP algorithm
    • Karlsruhe: University of Karlsruhe
    • RIEDMILLER M, BRAUN H. A direct adaptive method for faster backpropagation learning: The RPROP algorithm [R]. Karlsruhe: University of Karlsruhe, 1992.
    • (1992)
    • Riedmiller, M.1    Braun, H.2
  • 10
    • 0027205884 scopus 로고
    • A scaled conjugate gradient algorithm for fast supervised learning
    • MOLLER M F. A scaled conjugate gradient algorithm for fast supervised learning [J]. Neural Networks, 1993, 6(4): 525-533.
    • (1993) Neural Networks , vol.6 , Issue.4 , pp. 525-533
    • Moller, M.F.1
  • 11
    • 0001024110 scopus 로고
    • First and second order methods for learning: Between steepest descent and Newton's method
    • BATTITI R. First and second order methods for learning: Between steepest descent and Newton's method [J]. Neural Computation, 1992, 4: 141-166.
    • (1992) Neural Computation , vol.4 , pp. 141-166
    • Battiti, R.1
  • 12
    • 0043098510 scopus 로고    scopus 로고
    • A comparison of nonlinear optimization strategies for feedforward adaptive layered networks
    • WEBB A R, LOWE D, BEDWORTH M D. A comparison of nonlinear optimization strategies for feedforward adaptive layered networks [J]. Royal Signals and Radar Establishment, 1998, 6: No.4157.
    • (1998) Royal Signals ando Radar Establishment , vol.6
    • Webb, A.R.1    Lowe, D.2    Bedworth, M.D.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.