Capability assessment of conventional and data-driven models for prediction of suspended sediment load
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11356-022-18594-4.pdf
Reference68 articles.
1. Adib A, Mahmoodi A (2017) Prediction of suspended sediment load using ANN GA conjunction model with Markov chain approach at flood conditions. KSCE J Civ Eng 21:447–457. https://doi.org/10.1007/s12205-016-0444-2
2. Akande KO, Owolabi TO, Olatunji SO, Abdul Raheem A (2017) hybrid particles warm optimization and support vector regression model for modelling permeabilityprediction of hydrocarbon reservoir. J Pet Sci Eng 150:43–53
3. Ali SH (2012) Miner for OACCR: Case of medical data analysis in knowledge discovery," IEEE, 2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), Sousse, pp. 962–975. https://doi.org/10.1109/SETIT.2012.6482043
4. Ali SH (2013) Novel Approach for Generating the key of stream cipher system using random forest data mining algorithm, Sixth International Conference on Developments in eSystems Engineering, Abu Dhabi, pp. 259–269. https://doi.org/10.1109/DeSE.2013.54
5. Alizadeh MJ, Kavianpou MR, Kisi O, Nourani V (2017) A new approach for simulating and forecasting the rainfall-runoff process within the next two months. J Hydrol 548:588–597. https://doi.org/10.1016/j.jhydrol.2017.03.032
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