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Volumn , Issue , 2010, Pages 1265-1268

Rainfall prediction using generalized regression neural network: Case study Zhengzhou

Author keywords

BP neural network; Generalized regression neural network; Prediction; Rainfall

Indexed keywords

ANNUAL RAINFALL; ARTIFICIAL NEURAL NETWORKS; BACK PROPAGATION NEURAL NETWORKS; BP NEURAL NETWORKS; ENGINEERING FIELDS; GENERALIZED REGRESSION NEURAL NETWORKS; HYDROLOGIC TIME SERIES; LINEAR MODEL; NETWORK STRUCTURES; PERFECT MODEL; PREDICTION; PREDICTION AND FORECASTING; PREDICTION ERRORS; RAINFALL; RAINFALL PREDICTION; SIMULATION RESULT; STEPWISE REGRESSION ANALYSIS; STEPWISE REGRESSION METHOD;

EID: 79952426701     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCIS.2010.312     Document Type: Conference Paper
Times cited : (32)

References (6)
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  • 4
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    • River flow forecasting with artificial neural networks using satellite observed precipitation pre-processed with flow length and travel time information: Case study of the Ganges river basin
    • Akhtar M. K., Corzo G. A., van Andel S. J., and Jonoski A., "River flow forecasting with artificial neural networks using satellite observed precipitation pre-processed with flow length and travel time information: case study of the Ganges river basin", Hydrol. Earth Syst. Sci., (13), 1607-1618, 2009.
    • (2009) Hydrol. Earth Syst. Sci. , Issue.13 , pp. 1607-1618
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  • 6
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    • An artificial neural network model for rainfall forecasting in Bangkok, Thailand
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    • Hung, N.Q.1    Babel, M.S.2    Weesakul, S.3    Tripath, N.K.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.