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• W2919972822 abstract "Algal atypical proliferation is a consequence of water fertilization (also called eutrophication) and one of the main causes of the degradation of reservoir and lake ecosystems. Its intensification during the last decades has led the stakeholders to seek water management and restoration solutions, including those based on modelling approaches. In this way, this paper presents one reservoir eutrophication modelling based on a new hybrid algorithm that combines multivariate adaptive regression splines (MARS) and differential evolution (DE) to estimate the algal abnormal proliferation from physical-chemical and biological variables. This technique involves the optimization of the MARS hyperparameters during the training process. Additionally, an M5 model tree was fitted to the experimental data for comparison purposes. Apart from successfully forecasting algal atypical growth (coefficients of determination equal to 0.83 and 0.91), the model showed here can establish the significance of each biological and physical-chemical parameter of the algal enhanced growth. Finally, the main conclusions of this research work are exposed." @default.
• W2919972822 created "2019-03-11" @default.
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• W2919972822 creator A5081466386 @default.
• W2919972822 date "2019-05-01" @default.
• W2919972822 modified "2023-10-17" @default.
• W2919972822 title "Modeling algal atypical proliferation using the hybrid DE–MARS–based approach and M5 model tree in La Barca reservoir: A case study in northern Spain" @default.
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• W2919972822 doi "https://doi.org/10.1016/j.ecoleng.2019.02.020" @default.
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