Estimating Daily Pan Evaporation Using Different Data-Driven Methods and Lag-Time Patterns

By Sungwon Kim, Jalal Shiri, Ozgur Kisi, Vijay P. Singh. Water resources management, 2013

83 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Atmospheric Science, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/82c80827cbac49dd09063fc4c856d9530010a701

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Roozbeh Moazenzadeh
2. Kwok-Wing Chau
3. Babak Mohammadi
4. Shahaboddin Shamshirband

In Atmospheric Science

1. Babak Mohammadi
2. Roozbeh Moazenzadeh
3. Kwok-Wing Chau
4. Shahaboddin Shamshirband

In Environmental Engineering

1. Babak Mohammadi
2. Kwok-Wing Chau
3. Shahaboddin Shamshirband
4. Roozbeh Moazenzadeh
5. Ozgur Kisi
6. Hossein Bonakdari
7. Isa Ebtehaj
8. U. Aksoy

Citations in the corpus

• Coupling a firefly algorithm with support vector regression to predict evaporation in northern Iran (2018, methodology): “Kim et al. (2013) predicted evaporation values on a daily scale at the Daegu and Ulsan meteorological stations in South Korea and report satisfactory performance for all three of their methods; using a generalized regression neural networks model (GRNNM), an adaptive neurofuzzy inference system…”