SVR-based prediction of evaporation combined with chaotic approach

By Özlem Baydaroğlu, K. Koçak. 2014

77 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/fe657193ac5019e4738cc749f1b32ca26da2a031

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. 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

In Global and Planetary Change

1. Babak Mohammadi
2. Roozbeh Moazenzadeh
3. Kwok-Wing Chau
4. Shahaboddin Shamshirband
5. Ozgur Kisi
6. U. Aksoy
7. B. B. Ekici

Citations in the corpus

• Coupling a firefly algorithm with support vector regression to predict evaporation in northern Iran (2018, methodology): “Ghafari Gousheh, Piri, Amin, & Han, 2009; Taormina, Chau, & Sivakumar, 2015; Wu & Chau, 2006). The ANN is an effective tool for modeling nonlinear systems as it does not require complex mathematical equations to be defined for the phenomenon under study. This technique has been widely used for predi”