Author:
Selvaraj Venkatesan,Saradhambal Singarasubramanian Ramachandran,Pandu Parthasarathy,Aloysius Ajin Bejino,Vijayaprabhakaran Krishnan
Publisher
Springer Nature Switzerland
Reference74 articles.
1. Ahmad S, Babak HSAS, Davide M, Mundher YZ (2020) Application of newly developed ensemble machine learning models for daily suspended sediment load prediction and related uncertainty analysis. Hydrol Sci J 65(12):2022–2042
2. Al Dahoul N, Ahmed AN, Allawi MF, Sherif M, Sefelnasr A, Chau K-W, El-Shafie A (2022) A comparison of machine learning models for suspended sediment load classification. Eng Appl Comput Fluid Mech 16(01):1211–1232
3. Atikur Rahman M, Hossain A, Riazul Islam M, Azim A, Gaber A, Aftab T (2022) Chapter 22 - Metals and metalloids stress in plants: microorganisms and phytoremediation based mitigation strategies. Metals Metalloids Soil Plant Water Syst Phytophysiol Remediation Techniques 445–484. https://doi.org/10.1016/B978-0-323-91675-2.00009-3
4. Augustsson C (2021) Influencing factors on petrography interpretations in provenance research a case-study review. Geosciences 11(5):205. Available from: https://doi.org/10.3390/geosciences11050205
5. Avramidis P, Samiotis A, Kalimani E, Papoulis D, Lampropouu P, Bekiari V (2013) Sediment charnockitesand the water physic—chemical parameters of the Lysimachia Lake, western Greece‛. Environ Earth Sci 70(2):383–392