10 citations as recorded by crossref.

1. A quantity-distribution synthesized framework for risk assessment of algal blooms T. Zhou et al. 10.1016/j.jhydrol.2023.129869
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3. Bayesian Network Structural Learning Using Adaptive Genetic Algorithm with Varying Population Size R. Rodrigues Mendes Ribeiro & C. Dias Maciel 10.3390/make5040090
4. Predicting Imminent Cyanobacterial Blooms in Lakes Using Incomplete Timely Data C. Heggerud et al. 10.1029/2023WR035540
5. A CPSOCGSA-tuned neural processor for forecasting river water salinity: Euphrates river, Iraq Z. Khudhair et al. 10.1080/23311916.2022.2150121
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7. Predicting coastal harmful algal blooms using integrated data-driven analysis of environmental factors Z. Yan et al. 10.1016/j.scitotenv.2023.169253
8. Nutrient reduction mitigated the expansion of cyanobacterial blooms caused by climate change in Lake Taihu according to Bayesian network models J. Deng et al. 10.1016/j.watres.2023.119946
9. A Comprehensive Survey of Machine Learning Methodologies with Emphasis in Water Resources Management M. Drogkoula et al. 10.3390/app132212147
10. A systems approach to modelling phosphorus pollution risk in Scottish rivers using a spatial Bayesian Belief Network helps targeting effective mitigation measures M. Glendell et al. 10.3389/fenvs.2022.976933