Multivariate modeling of groundwater quality using hybrid evolutionary soft-computing methods in various climatic condition areas of Iran
In the current study, several soft-computing methods including artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), gene expression programming (GEP), and hybrid wavelet theory-GEP (WGEP) are used for modeling the groundwater's electrical conductivity (EC) variable....
Guardado en:
Autores principales: | Alireza Emadi, Sarvin Zamanzad-Ghavidel, Reza Sobhani, Ali Rashid-Niaghi |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
IWA Publishing
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/b4854af995894ea198a82c92e5f0b947 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis
por: Yueling Ma, et al.
Publicado: (2021) -
GRNN Model for prediction of groundwater fluctuation in the state of Uttarakhand of India using GRACE data under limited bore well data
por: Dilip Kumar, et al.
Publicado: (2021) -
Calculating groundwater mixing ratios in multi-aquifers based on statistical methods: a case study
por: Song Chen, et al.
Publicado: (2021) -
Interaction of hydro-socio-technology-knowledge indicators in integrated water resources management using soft-computing techniques
por: Masoumeh Zeinali, et al.
Publicado: (2021) -
Prediction of groundwater flow in shallow aquifers using artificial neural networks in the northern basins of Algeria
por: N. Guezgouz, et al.
Publicado: (2021)