Comparison of Wavelet-Based ANN and Regression Models for Reservoir Inflow Forecasting
By K. Budu. 2014
82 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering, Environmental Engineering, Water Science and Technology
View Paper: https://www.semanticscholar.org/paper/e92c128267c8117ec0a1e7a6e3da300edb7fc666
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
- Jan Adamowski
- Vahid Nourani
- A. H. Baghanam
- Ozgur Kisi
- Kwok-Wing Chau
- Masoud Karbasi
- Ravinesh C. Deo
- C. Wu
In Environmental Engineering
- Jan Adamowski
- A. H. Baghanam
- Vahid Nourani
- Ozgur Kisi
- Kwok-Wing Chau
- Masoud Karbasi
- Ravinesh C. Deo
- Mukesh Tiwari
In Water Science and Technology
- Jan Adamowski
- Vahid Nourani
- A. H. Baghanam
- Ozgur Kisi
- Masoud Karbasi
- Kwok-Wing Chau
- Ravinesh C. Deo
- John M. Quilty
Citations in the corpus
- Applications of hybrid wavelet–Artificial Intelligence models in hydrology: A review (2014, methodology): “Krishna (2013) explored the capability of two pre-processing techniques of wavelets and MA in combination with ANN and MLR models for prediction of daily inflow values.”