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Volumn 218 CCIS, Issue PART 5, 2011, Pages 262-266

A study on a new method for the analysis of flood risk assessment based on artificial neural network

Author keywords

back propagation; flood; neural network; risk assessment

Indexed keywords

APPLICATION PROSPECT; ARTIFICIAL NEURAL NETWORK; BP ARTIFICIAL NEURAL NETWORK; COMPOSITE METHOD; EVALUATION RESULTS; FLOOD DISASTER; FLOOD RISK ANALYSIS; FLOOD RISK ASSESSMENTS; GRADE CRITERION; HENAN PROVINCE; MULTI-DIMENSIONAL SPACE; NONUNIFORMITY; REAL NUMBER;

EID: 80052369744     PISSN: 18650929     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-23357-9_47     Document Type: Conference Paper
Times cited : (2)

References (5)
  • 3
    • 0036604737 scopus 로고    scopus 로고
    • Estimation of all-terminal network reliability using an artificial neural network
    • Chat, S.R., Abdullah, K.: Estimation of all-terminal network reliability using an artificial neural network. Computers and Operations Research 29, 849-868 (2002)
    • (2002) Computers and Operations Research , vol.29 , pp. 849-868
    • Chat, S.R.1    Abdullah, K.2
  • 4
    • 33845414060 scopus 로고    scopus 로고
    • Projection pursuit model for evaluating grade of flood disaster loss
    • Jin, J.L., Zhang, X.L., Ding, J.: Projection Pursuit Model for Evaluating Grade of Flood Disaster Loss. Systems Engineering-theory & Practice 22(2), 140-144 (2002)
    • (2002) Systems Engineering-theory & Practice , vol.22 , Issue.2 , pp. 140-144
    • Jin, J.L.1    Zhang, X.L.2    Ding, J.3
  • 5
    • 46649105382 scopus 로고    scopus 로고
    • A practical scheme for establishing grade model of flood disaster loss
    • Jin, J.L., Jin, B.M., Yang, X.H., Ding, J.: A practical scheme for establishing grade model of flood disaster loss. Journal of Catastrophology 15(2), 1-6 (2000)
    • (2000) Journal of Catastrophology , vol.15 , Issue.2 , pp. 1-6
    • Jin, J.L.1    Jin, B.M.2    Yang, X.H.3    Ding, J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.