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Volumn 19, Issue , 2011, Pages 1-12

Neural network application for monthly precipitation data reconstruction

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; DATA SET; ERROR ANALYSIS; HYDROLOGICAL CHANGE; PERFORMANCE ASSESSMENT; PRECIPITATION INTENSITY;

EID: 79954497899     PISSN: 10583912     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (11)

References (19)
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  • 3
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  • 5
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    • Comparison of neural network methods for infilling missing daily weather records
    • Coulibaly, P., and N.D. Evora. 2007. Comparison of neural network methods for infilling missing daily weather records. Journal of Hydrology, Vol. 341, pp. 27-41.
    • (2007) Journal of Hydrology , vol.341 , pp. 27-41
    • Coulibaly, P.1    Evora, N.D.2
  • 6
    • 0032584497 scopus 로고    scopus 로고
    • High resolution studies of rainfall on Norfolk Island Part II: Interpolation of rainfall data
    • Dirks, K.N., J.E. Hay, C.D. Stow, and D. Harris. 1998. High resolution studies of rainfall on Norfolk Island Part II: interpolation of rainfall data. J. Hydrol., Vol. 208(3-4), pp. 187-193.
    • (1998) J. Hydrol , vol.208 , Issue.3-4 , pp. 187-193
    • Dirks, K.N.1    Hay, J.E.2    Stow, C.D.3    Harris, D.4
  • 7
    • 0034696138 scopus 로고    scopus 로고
    • Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall
    • Goovaerts, P. 2000. Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. J. hydrol, Vol. 228(2000), pp. 113-129.
    • (2000) J. Hydrol , vol.228 , Issue.2000 , pp. 113-129
    • Goovaerts, P.1
  • 9
    • 0032483944 scopus 로고    scopus 로고
    • Spatial interpolation of climatic Normal's: Test of a new method in the canadian boreal forest
    • Nalder I.A., and R.W. Wein. 1998. Spatial interpolation of climatic Normal's: test of a new method in the Canadian boreal forest. Agricultural and Forest Meteorology, 92, pp. 211-225.
    • (1998) Agricultural and Forest Meteorology , vol.92 , pp. 211-225
    • Nalder, I.A.1    Wein, R.W.2
  • 11
    • 0005641297 scopus 로고    scopus 로고
    • Tehran university publications; Tehran
    • Mahdavi, M. 1998. Applied Hydrology, vol 1, Tehran university publications; Tehran.
    • (1998) Applied Hydrology , vol.1
    • Mahdavi, M.1
  • 15
    • 0038502200 scopus 로고    scopus 로고
    • Artificial neural networks for stream flow prediction
    • Dolling, O.R., and E.A. Varas. 2002. Artificial neural networks for stream flow prediction, Journal of Hydraulic Research.Vol. 40(5), pp. 547-554.
    • (2002) Journal of Hydraulic Research , vol.40 , Issue.5 , pp. 547-554
    • Dolling, O.R.1    Varas, E.A.2
  • 16
    • 34247576161 scopus 로고    scopus 로고
    • Spatiotemporal monthly rainfall reconstruction via artificial neural network - case study: South of Brazil Adv
    • Lucio, P.S., F.C. Conde, I.F.A. Cavalcanti, A.I. Serrano, A.M. Ramos, and A.O. Cardoso. 2007. Spatiotemporal monthly rainfall reconstruction via artificial neural network - case study: south of Brazil Adv. Geosci.,Vol. 10, pp. 67-76.
    • (2007) Geosci , vol.10 , pp. 67-76
    • Lucio, P.S.1    Conde, F.C.2    Cavalcanti, I.F.A.3    Serrano, A.I.4    Ramos, A.M.5    Cardoso, A.O.6
  • 17
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  • 18
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    • Simulation of seasonal precipitation and rain days over Greece: A statistical downscaling technique based on artificial neural networks (ANNs)
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    • Tolika, K.1    Maheras, P.2    Vafiadis, M.3    Flocas, H.A.4    Arseni-Papadimitriou, A.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.