Enhancement of Groundwater-Level Prediction Using an Integrated Machine Learning Model Optimized by Whale Algorithm

By F. B. Banadkooki, M. Ehteram, A. Ahmed, F. Teo, C. Fai, Haitham Abdulmohsin Afan, Michelle Sapitang, Ahmed El-Shafie. Natural Resources Research, 2020

96 citations recorded by the source corpus.

Subfields: Environmental Engineering, Global and Planetary Change, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/479b33a408dbdc7d52392c7e98c4080e121733a6

How researchers see this paper

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

In Environmental Engineering

1. Amir Mosavi
2. Kwok-Wing Chau
3. S. M. Bateni
4. Saeed Samadianfard
5. Ozgur Kisi
6. Hossein Bonakdari
7. Isa Ebtehaj
8. U. Aksoy

In Global and Planetary Change

1. Amir Mosavi
2. Kwok-Wing Chau
3. S. M. Bateni
4. Ozgur Kisi
5. U. Aksoy
6. B. B. Ekici

In Water Science and Technology

1. Amir Mosavi
2. Kwok-Wing Chau
3. Ozgur Kisi
4. U. Aksoy
5. B. B. Ekici

Citations in the corpus

• Groundwater level prediction in arid areas using wavelet analysis and Gaussian process regression (2021, methodology): “Campozano et al. (2020) investigated the capabilities of ANN to predict river discharge using wavelet analysis.”