Salim Heddam
Orcid: 0000-0002-8055-8463
According to our database1,
Salim Heddam
authored at least 13 papers
between 2016 and 2025.
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Bibliography
2025
Enhancing formation bulk density prediction while drilling using mud logging data and interpretable boosting machine learning.
Earth Sci. Informatics, January, 2025
An efficient data fusion model based on Bayesian model averaging for robust water quality prediction using deep learning strategies.
Expert Syst. Appl., 2025
Enhancing Pan evaporation predictions: Accuracy and uncertainty in hybrid machine learning models.
Ecol. Informatics, 2025
2024
Enhancing Streamflow Prediction Accuracy: A Comprehensive Analysis of Hybrid Neural Network Models with Runge-Kutta with Aquila Optimizer.
Int. J. Comput. Intell. Syst., December, 2024
New formulation for predicting total dissolved gas supersaturation in dam reservoir: application of hybrid artificial intelligence models based on multiple signal decomposition.
Artif. Intell. Rev., 2024
2023
River water temperature prediction using hybrid machine learning coupled signal decomposition: EWT versus MODWT.
Ecol. Informatics, December, 2023
Streamflow prediction in mountainous region using new machine learning and data preprocessing methods: a case study.
Neural Comput. Appl., April, 2023
Improving the accuracy of daily solar radiation prediction by climatic data using an efficient hybrid deep learning model: Long short-term memory (LSTM) network coupled with wavelet transform.
Eng. Appl. Artif. Intell., 2023
2022
Neurocomputing, 2022
2021
Estimating reference evapotranspiration using hybrid adaptive fuzzy inferencing coupled with heuristic algorithms.
Comput. Electron. Agric., 2021
Modelling daily soil temperature by hydro-meteorological data at different depths using a novel data-intelligence model: deep echo state network model.
Artif. Intell. Rev., 2021
2018
Modeling daily dissolved oxygen concentration using modified response surface method and artificial neural network: a comparative study.
Neural Comput. Appl., 2018
2016
Proceedings of the Intelligence Systems in Environmental Management: Theory and Applications, 2016