Daily Reference Evapotranspiration Estimation Based on Least Squares Support Vector Machines

Author:

Chen Dachun

Publisher

Springer Berlin Heidelberg

Reference16 articles.

1. Allen, R.G., Pereira, L.S., Raes, D., Smith, M.: Crop evapotranspiration: guidelines for computing crop water requirements. In: Proceedings of the Irrigation and Drainage Paper No. 56. Food and Agricultural Organization, United Nations, Rome (1998)

2. Kumar, M., Raghuwanshi, N.S., Singh, R., et al.: Estimating evapotranspiration using artificial neural network. Journal of Irrigation and Drainage Engineering 128, 224–233 (2002)

3. Trajkovic, S., Todorovic, B., Stankovic, M.: Forecasting of reference evapotranspiration by artificial neural networks. Journal of Irrigation and Drainage Engineering 129, 454–457 (2003)

4. Odhiambo, L.O., Yoder, R.E., Yoder, D.C., et al.: Optimization of fuzzy evapotranspiration model through neural training with input-output examples. Trans. ASAE American Society of Agricultural and Biological Engineering 44, 1625–1633 (2001)

5. Aksoy, H., Guven, A., Aytek, A., et al.: Discussion of Generalized regression neural networks for evapotranspiration modeling. Hydrological Sciences Journal 52, 825–831 (2007)

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