1 |
Jesen, M. E. (Ed), 1974. Consumptive use of water and irrigation water requirements. Rep. Tech, Comm. on Irrigation, p. 277.
|
2 |
Kang, M. S., and S. W. Park, 2003. Short-term flood forecasting using artificial neural networks. Journal of the Korean Society of Agricultural Engineers 45(2): 45-57 (in Korean).
|
3 |
Kisi, O., 2009. Daily pan evaporation modelling using multi-layer perceptions and radial basis neural networks. Hydrological Processes 23: 213-223. doi:10.1002/hyp.7126.
DOI
|
4 |
Kumar, M., N. S. Raghuwanshi, and R. Singh, 2011. Artificial neural networks approach in evapotranspiration modelling: a review. Irrigation Science 29: 11-25. doi:10.1007/s00271-010-0230-8.
DOI
|
5 |
Kumar, M., N. S. Ranghuwanshi, S. Singh, W. W. Wallender, and W. O. Pruitt, 2002. Estimating evapotranspiration using artificial neural network. Journal of Irrigation and Drainage 128(4): 224-233. doi:10.1061/(ASCE)0733-9437(2002)128:4(224).
DOI
|
6 |
Lee, E. J., M. S. Kang, J. A. Park, J. Y. Choi, and S. W. Park, 2010. Estimation of future reference crop evapotranspiration using artificial neural network. Journal of Korean Society of Agricultural Engineers 52(5): 1-9 (in Korean). doi:10.5389/KSAE.2010.52.5.001.
DOI
|
7 |
Makridakis, S., S. C. Wheelwright, and R. J. Hyndman, 1998. Forecasting-mothods and application (Third Ed.). Wiley, New York, pp. 42-50.
|
8 |
McVicker, R., 1982. The effects of model complexity on ther predictive accuracy of soil moisture accounting models M.S. Thesis, Utah State University, Logan, Utah.
|
9 |
Moon, J. W., C. G. Jung, and D. R. Lee, 2013. Parameter regionalization of Hargreaves equation based on climatological characteristics in Korea. Journal of Korea Water Resources Association 46(9): 933-946. doi:10.3741/JKWRA.2013.46.9.933.
DOI
|
10 |
Oh, S. K., 2008. Pattern recognition. Kyobo Moongo, Seoul, p. 98.
|
11 |
Trajkovic, S., 2005. Temperature-based approaches for estimating reference evapotranspiration. Journal of Irrigation and Drainage 131(4): 316-323. doi:10.1061/(ASCE)0733-9437(2005)131:4(316).
DOI
|
12 |
Salih, A. M. A., and U. Sendil, 1984. Evapotranspiration under extremely arid climates. Journal of Irrigation and Drainage 110(3): 289-303. doi:10.1061/(ASCE)0733-9437(1984)110:3(289).
DOI
|
13 |
Shih, S. F., 1984. Data requirement for evapotranspiration estimation. Journal of Irrigation and Drainage 110(3): 263-274. doi:10.1061/(ASCE)0733-9437(1984)110:3(263).
DOI
|
14 |
Sudheer, K. P., A. K. Gosain, and K. S. Ramasatri, 2003. Estimating actual evapotranspiration from limited climatic data using neural computing technique. Journal of Irrigation and Drainage 129(3): 214-218. doi:10.1080/09715010.2009.10514929.
DOI
|
15 |
Trajkovic, S., and S. Kolakovic, 2003. Estimating reference evapotranspiration using limited weather data. Journal of Irrigation and Drainage 45(2): 45-57. doi:10.1061/(ASCE)IR.1943-4774.0000094.
|
16 |
Gocic, M., and S. Trajkovic, 2010. Software for estimating reference evapotranspiration using limited weahter data. Computers and Electronics in Agriculture 71: 158-162. doi:10.1016/j.compag.2010.01.003.
DOI
|
17 |
Wang, Y. M., S. Traore, and T. Kerh, 2008. Neural network approach for estimating reference evapotranspirtion form limited climatic data in Burkina Faso. WSEA Transactions on Computers 6(7): 704-713.
|
18 |
Zanetti, S. S., E. F. Sousa, W. P. S. Oliveira, F. T. Almeida, and S. Bernardo, 2007. Estimating evapotranspiration using artificial neural network and minimum climatological data. Jousrnal of Irrigation and Drainage 133(2): 83-89. doi:10.1061/(ASCE)0733-9437(2007)133:2(83).
DOI
|
19 |
Allen, R. G., M. Smith, A. Perroer, and L. S. Preira, 1994. An update for the calculation of reference evapotranspiration. ICID Bull 43(2): 35-92.
|
20 |
APEC Cliamte Center, Clipped CMIP5 data, http://adss.apcc21.org/DataSet/CMIP5/cmip5,jsp. Accessed 31 Mar. 2017.
|
21 |
Hargreaves, G. H., 1975. Moisture availability and crop production. Transactions of ASAE 18(5): 980-984. doi:10.13031/2013.36722.
DOI
|
22 |
Hargreaves, H. G., and A. Z. Samani, 1985. Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture 1(2): 96-99. doi:10.13031/2013.26773.
DOI
|