Daily Pan Evaporation Estimation Using Heuristic Methods with Gamma Test

By Anurag Malik, Anil Kumar, Ozgur Kisi. Journal of irrigation and drainage engineering, 2018

46 citations recorded by the source corpus.

AbstractIn this study, radial basis neural network (RBNN), self-organizing map neural network (SOMNN), and multiple linear regression (MLR) are used for the estimation of daily pan evaporation at P...

Subfields: Atmospheric Science, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/69fa7140fb2017a5d382cff7dc18401326191b79

How researchers see this paper

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

In Atmospheric Science

1. Salim Heddam
2. Ozgur Kisi

In Environmental Engineering

1. Salim Heddam
2. Anurag Malik
3. Ozgur Kisi
4. Quoc Bao Pham
5. D. Souag-Gamane
6. Y. Tikhamarine
7. Jan Adamowski
8. Kwok-Wing Chau

In Global and Planetary Change

1. Salim Heddam
2. Ozgur Kisi
3. Anurag Malik
4. D. Souag-Gamane
5. Y. Tikhamarine
6. Quoc Bao Pham
7. Masoud Karbasi
8. Hossein Bonakdari

Citations in the corpus

• Evaporation modelling by heuristic regression approaches using only temperature data (2019, methodology): “Malik et al. (2018) applied two different data-driven methods using maximum and minimum temperature (Tmin and Tmax), relative humidity, wind speed and sunshine hours as inputs.”
• Support vector regression optimized by meta-heuristic algorithms for daily streamflow prediction (2020, methodology): “Then it was employed by other scholars (Tsui et al. 2002; Remesan et al. 2008; Moghaddamnia et al. 2009; Noori et al. 2011; Kakaei Lafdani et al. 2013; Malik et al. 2017b, 2018, 2020a, c).”