Machine learning-based evolution of water quality prediction model: an integrated robust framework for comparative application on periodic return and jitter data

Environmental Pollution, Journal Year: 2025, Volume and Issue: unknown, P. 125834 - 125834

Published: Feb. 1, 2025

Language: Английский

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Applying Multivariate Analysis and Machine Learning Approaches to Evaluating Groundwater Quality on the Kairouan Plain, Tunisia

Water, Journal Year: 2023, Volume and Issue: 15(19), P. 3495 - 3495

Published: Oct. 6, 2023

In the Zeroud basin, a diverse array of methodologies were employed to assess, simulate, and predict quality groundwater intended for irrigation. These included irrigation water indices (IWQIs); intricate statistical analysis involving multiple variables, supported with GIS techniques; an artificial neural network (ANN) model; XGBoost regression model. Extensive physicochemical examinations performed on samples elucidate their compositional attributes. The results showed that abundance order ions was Na+ > Ca2+ Mg2+ K+ SO42− HCO3− Cl−. facies reflected Ca-Mg-SO4, Na-Cl, mixed Ca-Mg-Cl/SO4 types. A cluster (CA) principal component (PCA), along ionic ratios, detected three different characteristics. mechanisms controlling chemistry revealed water–rock interaction, dolomite dissolution, evaporation, ion exchange. assessment agriculture respect IWQIs, such as index (IWQI), sodium adsorption ratio (SAR), percentage (Na%), soluble (SSP), potential salinity (PS), residual carbonate (RSC), domination valuable agriculture. However, IWQI PS fell between high-to-severe restrictions injurious-to-unsatisfactory. ANN models robust predicting IWQIs. For example, ANN-HyC-9 emerged most precise forecasting framework according its outcomes, it showcased link prime attributes IWQI. nine this model hold immense significance in prediction. R2 values training testing data stood at 0.999 (RMSE = 0.375) 0.823 3.168), respectively. findings indicate XGB-HyC-3 accurate model, displaying stronger connection exceptional When IWQI, approximately model’s played pivotal role. Notably, yielded 0.001) 0.913 2.217) datasets, Overall, these offer significant details decision-makers managing can support long-term use resources.

Language: Английский

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Microbial synthesis of titanium dioxide nanoparticles and their importance in wastewater treatment and antimicrobial activities: a review

Frontiers in Microbiology, Journal Year: 2023, Volume and Issue: 14

Published: Oct. 16, 2023

Nanotechnology (NT) and nanoparticles (NPs) have left a huge impact on every field of science today, but they shown tremendous importance in the fields cosmetics environmental cleanup. NPs with photocatalytic effects positive responses wastewater treatment, cosmetics, biomedical field. The chemically synthesized TiO2 (TiO2 NPs) utilize hazardous chemicals to obtain desired-shaped TiO2. So, microbial-based synthesis has gained popularity due its eco-friendly nature, biocompatibility, etc. Being NPs, high surface area-to-volume ratio addition their degradation nature. In present review, authors emphasized microbial (algae, bacterial, fungi, virus-mediated) NPs. Furthermore, exhibited food sector, automobile, aerospace, medical,

Language: Английский

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Hybrid machine learning models for prediction of daily dissolved oxygen

Journal of Water Process Engineering, Journal Year: 2023, Volume and Issue: 54, P. 103957 - 103957

Published: June 27, 2023

Language: Английский

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Melatonin-mediated nitric oxide signaling enhances adaptation of tomato plants to aluminum stress

South African Journal of Botany, Journal Year: 2023, Volume and Issue: 162, P. 443 - 450

Published: Sept. 26, 2023

Language: Английский

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Understanding groundwater mineralization controls and the implications on its quality (Southwestern Ghana): insights from hydrochemistry, multivariate statistics, and multi-linear regression models

Acta Geophysica, Journal Year: 2024, Volume and Issue: 72(5), P. 3563 - 3580

Published: Jan. 17, 2024

Language: Английский

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Dissolved oxygen prediction using regularized extreme learning machine with clustering mechanism in a black bass aquaculture pond

Aquacultural Engineering, Journal Year: 2024, Volume and Issue: 105, P. 102408 - 102408

Published: Feb. 5, 2024

Language: Английский

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Investigating the nexus between energy, socio-economic factors and environmental pollution: A geo-spatial multi regression approach

Gondwana Research, Journal Year: 2024, Volume and Issue: 130, P. 308 - 325

Published: March 1, 2024

Language: Английский

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Machine learning driven forecasts of agricultural water quality from rainfall ionic characteristics in Central Europe

Agricultural Water Management, Journal Year: 2024, Volume and Issue: 293, P. 108690 - 108690

Published: Jan. 21, 2024

Sodium hazard poses a critical threat to agricultural production globally and regionally which has been previously predicted from ground or surface water. Monitoring rainwater quality in this context is ignored but essential for water management central Europe. Our study focused predict sodium adsorption ratio (SAR) 1985 2021 ten ionic species of (pH, EC, Cl-, SO4−2, NO3-, NH4+, Na+, K+, Mg2+, Ca2+) employing four machine learning (random forest (RF), gaussian process regression (GU), random subspace (RSS), artificial neural network-multilayer perceptron (ANN-MLP)) methods at three stations K-puszta (KP), Farkasfa (FAK), Nyirjes (NYR) Hungary, Exploratory data analysis was performed using the Mann-Kendall test, Pearson correlation, principal component (PCA). Rainwater composition revealed highest percentage SO4−2 ions i.e., 21 31%, followed by 10 15% Na+ ions. test significant (p < 0.05) increasing trend SAR portraying it serious limiting production. Machine results model runs all algorithms prediction KP station proved efficacy ANN-MLP as superior with RMSE range 0.02 0.05, RF 0.14 0.19 scenario 2 (SC-2) (Na+, Ca2+). Validation best-selected algorithm (ANN-MLP) also low 0.08 0.05 both FAK NYR stations, respectively. Hence, efficiency forecasting proves be meticulous tool enhancing practices Central Europe resource crop future.

Language: Английский

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Temporal prediction of dissolved oxygen based on CEEMDAN and multi-strategy LSTM hybrid model

Environmental Earth Sciences, Journal Year: 2024, Volume and Issue: 83(6)

Published: March 1, 2024

Language: Английский

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