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Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches
Water quality indexes (WQI) are pivotal in assessing aquatic systems. Conventional
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …
[HTML][HTML] Predicting quality parameters of wastewater treatment plants using artificial intelligence techniques
Estimating wastewater treatment plants'(WWTPs) influent parameters such as 5-day
biological oxygen demand (BOD 5) and chemical oxygen demand (COD) is vital for …
biological oxygen demand (BOD 5) and chemical oxygen demand (COD) is vital for …
[HTML][HTML] A sophisticated model for rating water quality
Here, we present the Irish Water Quality Index (IEWQI) model for assessing transitional and
coastal water quality in an effort to improve the method and develop a tool that can be used …
coastal water quality in an effort to improve the method and develop a tool that can be used …
Extent of anthropogenic influence on groundwater quality and human health-related risks: an integrated assessment based on selected physicochemical …
The majority of people living on earth rely on groundwater as their primary supply of water
for daily needs. However, human activities continuously threaten this natural resource. In an …
for daily needs. However, human activities continuously threaten this natural resource. In an …
Data-driven soft computing modeling of groundwater quality parameters in southeast Nigeria: comparing the performances of different algorithms
JC Egbueri, JC Agbasi - Environmental Science and Pollution Research, 2022 - Springer
In recent decades, the simulation and modeling of water quality parameters have been
useful for monitoring and assessment of the quality of water resources. Moreover, the use of …
useful for monitoring and assessment of the quality of water resources. Moreover, the use of …
[HTML][HTML] Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches
Assessing eutrophication in coastal and transitional waters is of utmost importance, yet
existing Trophic Status Index (TSI) models face challenges like multicollinearity, data …
existing Trophic Status Index (TSI) models face challenges like multicollinearity, data …
Evolution of neural network to deep learning in prediction of air, water pollution and its Indian context
The scenario of developed and develo** countries nowadays is disturbed due to modern
living style which affects environment, wildlife and natural habitat. Environmental quality has …
living style which affects environment, wildlife and natural habitat. Environmental quality has …
Combination of discretization regression with data-driven algorithms for modeling irrigation water quality indices
PK Singh, J Rajput, D Kumar, V Gaddikeri… - Ecological …, 2023 - Elsevier
Forecasting water quality parameters helps plan crop selection and irrigation strategies but
is often costly because many parameters are required, particularly in develo** nations …
is often costly because many parameters are required, particularly in develo** nations …
The potential of big data and machine learning for ground water quality assessment and prediction
Water, a priceless gift from nature, acts as Earth's matrix, medium, and life-sustaining
substance. While the planet is predominantly covered by water, only 3% is available as …
substance. While the planet is predominantly covered by water, only 3% is available as …
[HTML][HTML] A study of assessment and prediction of water quality index using fuzzy logic and ANN models
Various human activities have been the main causes of surface water pollution. The uneven
distribution of industrial enterprises in the territories of the main river basins of Ukraine do …
distribution of industrial enterprises in the territories of the main river basins of Ukraine do …