Estimating evaporation using ANFIS
| Autor: | M. Erol Keskin, E. Dilek Taylan, Özlem Terzi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2006 |
| Předmět: |
Hydrology
Adaptive neuro fuzzy inference system Artificial neural network Meteorology Fuzzy set Evaporation Agricultural and Biological Sciences (miscellaneous) Water resources Variable (computer science) Scientific method Environmental science Relative humidity Water Science and Technology Civil and Structural Engineering |
| Popis: | Water resources engineering assessment requires simple but effective evaporation estimation procedures, especially from readily measurable meteorological factors. Unfortunately, such approaches are rather scarce in the literature. In this paper, an adaptive neural-based fuzzy inference system (ANFIS) was applied to daily meteorology data from the Lake Egirdir region in the southwestern part of Turkey. Daily evaporation, solar radiation, air and water temperatures, and relative humidity measurements were used to develop the ANFIS method, which helps to assess possible contributions that each input variable has on the evaporation estimates. Such an assessment is not possible by any conventional procedure including the Penman method. However, the Penman method daily evaporation estimations were used as output data for the verification of the ANFIS approach. Classical evaporation estimation models treat the data individually. However, ANFIS models process past data collectively and then adaptively provide est... |
| Databáze: | OpenAIRE |
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