Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran

By Mohammad Ali Ghorbani, Ravinesh C. Deo, Zaher Mundher Yaseen, Mahsa Hasanpour Kashani, Babak Mohammadi. Theoretical and Applied Climatology, 2018

184 citations recorded by the source corpus.

Subfields: Atmospheric Science, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/861faf4ee674c2c738d4680f85b55d5e59ba21c5

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. Ozgur Kisi
2. Babak Mohammadi
3. Salim Heddam
4. Babak Jahani
5. Ravinesh C. Deo

In Environmental Engineering

1. Babak Mohammadi
2. Ravinesh C. Deo
3. Ozgur Kisi
4. Zaher Mundher Yaseen
5. Salim Heddam
6. Babak Jahani
7. Mohammad Ali Ghorbani
8. Vahid Karimi

Citations in the corpus

• Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir, Turkey (2018, methodology): “…potential optimization method, since this tool has been shown to be an ideal utility used to enhance the performance of the artificial intelligence-based models in a number of recent studies, particularly in hydrological modelling (Ghorbani et al. 2017a, b; Raheli et al. 2017; Yaseen et al. 2017).”
• A comparison between the application of empirical and ANN methods for estimation of daily global solar radiation in Iran (2018, methodology): “…surveys carried out for studying the feasibility of different optimization algorithms for improving the ANN modeling of Rs, which suggest that the performance of ANN-based models can be improved considerably by coupling them with an optimization algorithm (Ghorbani et al. 2017; Deo et al. 2018).”
• Evaporation modelling by heuristic regression approaches using only temperature data (2019, methodology): “Ghorbani et al. (2017) proposed a new hybrid model, the multilayer perceptron–firefly algorithm (MLP-FFA), for predicting daily Epan in the arid regions of Iran.”
• Long-term monthly average temperature forecasting in some climate types of Iran, using the models SARIMA, SVR, and SVR-FA (2019, background): “In recent years, the use of combined Firefly algorithm (FA) has yielded favorable results based on artificial intelligence forecast methods for modeling in hydrology (Mohammadi et al. 2015; Ghorbani et al. 2018), water resources management (Moazenzadeh et al.”