A catchment-scale model of river water quality by Machine Learning Author links open overlay panelMaria Grazia Zanoni, Bruno Majone, Alberto BellinShow more Add to Mendeley Share Cite https://doi.org/10.1016/j.scitotenv.2022.156377Get rights and content...
Studies on surface water spectral features and modified model methods have shown that it is possible to perform water quality parameter monitoring by applying remote sensing technologies to more water quality variables with higher precision. Single water quality parameters such as chlorophyll-a, total su...
Water Quality Analysis Using Machine Learning Techniques The most crucial resource that must be preserved by humans is water. Due to numerous environmental and societal causes, the quality of the water is deterio... M Kumar,T Gobinath,MS Karthikeyan,... - International Conference on Deep Sciences...
The results of this study have also demonstrated that the machine learning models are efficient tools for accurately predicting the quality of irrigation water by only using the parameters that can be directly measured in a short time. Consequently, the implementation of the automated sensor ...
Groundwater quality (GWQ) monitoring is one of the best environmental objectives due to recent droughts and urban and rural development. Therefore, this study aimed to map GWQ in the central plateau of Iran by validating machine learning algorithms (MLAs) using game theory (GT). On this basi...
the highest R2values were similarly recorded for SSP by all regression models applied; this is also true among the machine learning models. Based on the classification of the SI index, the SVR, XGB and RF values were less than 0.1 which suggest excellent models for all water quality indices ...
The water quality prediction performance of machine learning models may be not only dependent on the models, but also dependent on the parameters in data set chosen for training the learning models. Moreover, the key water parameters should also be identified by the learning models, in order to...
Applying Machine Learning Techniques in Air Quality Prediction—A Bucharest City Case Study. Sustainability (Switzerland), 2023, 15(11): 8445. DOI:10.3390/su15118445 67. Cheng, H., Cheng, Y., Zheng, Y. et al. Prediction of irregular wave (current)-induced pore water pressure around mono...
Furthermore, a machine learning algorithm is developed for the qualitative and quantitative detection of multiple contaminants, achieving high accuracy (92.3%) and specificity (89.3%) without the need for preliminary processing of Raman spectra. This work provides a promising nanoengineering solution for...
Understanding and predicting the quality of inland waters are challenging, particularly in the context of intensifying climate extremes expected in the future. These challenges arise partly due to complex processes that regulate water quality, and arduou