# Prediction of irrigation groundwater quality parameters using ANN, LSTM, and MLR models

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/prediction-of-irrigation-groundwater-quality-parameters-using-ann-lstm-and-mlr/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Saber Kouadri,Chaitanya B. Pande,Balamurugan Panneerselvam,Kanak N. Moharir,Ahmed Elbeltagi |
| Citations | 181 |
| DOI | 10.1007/s11356-021-17084-3 |
| Fields | Engineering,Environmental Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3214254203 |
| PMID | 34748181 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Ahmed Elbeltagi](https://scholariq.org/researchers/ahmed-elbeltagi/)

## Paper journal

- [Environmental Science and Pollution Research](https://scholariq.org/journals/environmental-science-and-pollution-research/)

## Paper primary topic

- [Hydrological Forecasting Using AI](https://scholariq.org/topics/hydrological-forecasting-using-ai/)

## Paper topics

- [Hydrological Forecasting Using AI](https://scholariq.org/topics/hydrological-forecasting-using-ai/)
- [Hydrology and Drought Analysis](https://scholariq.org/topics/hydrology-and-drought-analysis/)
- [Water resources management and optimization](https://scholariq.org/topics/water-resources-management-and-optimization/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.