Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models

By Ravinesh C. Deo, Pijush Samui, Dookie Kim. Stochastic environmental research and risk assessment (Print), 2016

137 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/867b7f7671c57db3be7699ce98e891d9803d1e07

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. Zaher Mundher Yaseen
2. Mohammad Ali Ghorbani
3. Babak Mohammadi
4. Ravinesh C. Deo

In Electrical and Electronic Engineering

1. Zaher Mundher Yaseen
2. Mohammad Ali Ghorbani
3. Mahsa Hasanpour Kashani
4. Babak Mohammadi
5. Ravinesh C. Deo

In Environmental Engineering

1. Babak Mohammadi
2. Zaher Mundher Yaseen
3. Mohammad Ali Ghorbani
4. Ravinesh C. Deo
5. Ozgur Kisi
6. Salim Heddam
7. Anurag Malik
8. Anil Kumar

Citations in the corpus

• Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran (2018, methodology): “, physically based) parametric methods (Ch et al. 2014; Deo and Şahin 2015; Deo et al. 2015).”