Machine learning in natural and engineered water systems

Water Research, Journal Year: 2021, Volume and Issue: 205, P. 117666 - 117666

Published: Sept. 14, 2021

Language: Английский

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A novel hybrid BPNN model based on adaptive evolutionary Artificial Bee Colony Algorithm for water quality index prediction

Ecological Indicators, Journal Year: 2023, Volume and Issue: 146, P. 109882 - 109882

Published: Jan. 9, 2023

With the accelerated industrialization and urbanization process, water pollution in rivers is being increasingly worsened, has caused a series of ecological environmental issues. The prediction river quality index (WQI) prerequisite for prevention management. However, data non-smooth non-linear, strong coupling relationship between different parameters that influence each other observed, making it an inevitable problem to accurately predict parameters. To this end, combination machine learning intelligent optimization algorithms was hereby used break dilemma. Specifically, Back Propagation Neural Network (BPNN) model established using Artificial Bee Colony (ABC) algorithm, with three adaptive evolutionary strategies, i.e., dynamic factors, probability selection gradient initialization combined form Adaptive Evolutionary (AEABC) algorithm. experimental results algorithm demonstrate AEABC-BPNN only requires 14 iterations converge case. predictions WQI can reduce error evaluation indicators mean square (MSE) 0.2745, which at least 25.2% lower than those rest compared, absolute percentage (MAPE) 7.58%. In four WQIs, interval coverage (PICP) reaches 100%. Besides, robustness testing experiments were also designed verify still outperforms terms accuracy when guided by historical data. proposed plays pivotal role management lakes, scientific significance future protection.

Language: Английский

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Wildfire Damage Assessment over Australia Using Sentinel-2 Imagery and MODIS Land Cover Product within the Google Earth Engine Cloud Platform

Remote Sensing, Journal Year: 2021, Volume and Issue: 13(2), P. 220 - 220

Published: Jan. 10, 2021

Wildfires are major natural disasters negatively affecting human safety, ecosystems, and wildlife. Timely accurate estimation of wildfire burn areas is particularly important for post-fire management decision making. In this regard, Remote Sensing (RS) images great resources due to their wide coverage, high spatial temporal resolution, low cost. study, Australian affected by were estimated using Sentinel-2 imagery Moderate Resolution Imaging Spectroradiometer (MODIS) products within the Google Earth Engine (GEE) cloud computing platform. To end, a framework based on change analysis was implemented in two main phases: (1) producing binary map burned (i.e., vs. unburned); (2) estimating different Land Use/Land Cover (LULC) types. The first phase five steps: (i) preprocessing, (ii) spectral feature extraction pre-fire analyses; (iii) prediction detection differencing datasets; (iv) selection; (v) mapping selected features classifiers. second defining types LULC classes over global MODIS land cover product (MCD12Q1). Based test datasets, proposed showed potential detecting with an overall accuracy (OA) kappa coefficient (KC) 91.02% 0.82, respectively. It also observed that greatest area among related evergreen needle leaf forests burning rate 25 (%). Finally, results study good agreement Landsat products.

Language: Английский

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Surface water quality profiling using the water quality index, pollution index and statistical methods: A critical review

Environmental and Sustainability Indicators, Journal Year: 2023, Volume and Issue: 18, P. 100247 - 100247

Published: March 22, 2023

Surface water is heavily exposed to contamination as this the ubiquitous source for most of needs. This situation exaggerated by excessive population, heavy industrialization, rapid urbanization, and improper sanitation. Comprehensive measurement knowledge extraction surface quality therefore pivotal ensuring safe hygienic use. Consequently, profiling has received remarkable academic attention in recent decades that produces an ample amount research results. study, therefore, conducts a comprehensive systematic literature review summarize structure existing identify current trends hotspots. Reported results suggest terrain fresh includes 13 distinct sources are predominantly used 5 sectors. These sectors often cause pollution form industrial effluents, agricultural runoffs, domestic sewage. For quality, around 23 Water Quality Index (WQI) models, 10 Pollution (PI) models research. use several parameters. study reports exhaustive taxonomy 69 prominent parameters three categories which will support their adoption these models. Finally, limitations manual approaches summarized propose set seven requirements tech-intensive system development.

Language: Английский

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Biocompatible CaTiO3-PVDF composite-based piezoelectric nanogenerator for exercise evaluation and energy harvesting

Nano Energy, Journal Year: 2022, Volume and Issue: 102, P. 107682 - 107682

Published: Aug. 9, 2022

Language: Английский

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Analysis and prediction of water quality using deep learning and auto deep learning techniques

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 821, P. 153311 - 153311

Published: Jan. 19, 2022

Language: Английский

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Exploring potential machine learning application based on big data for prediction of wastewater quality from different full-scale wastewater treatment plants

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 832, P. 154930 - 154930

Published: April 4, 2022

Language: Английский

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Assessing and forecasting water quality in the Danube River by using neural network approaches

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 879, P. 162998 - 162998

Published: March 24, 2023

The health and quality of the Danube River ecosystems is strongly affected by nutrients loads (N P), degree contamination with hazardous substances or oxygen depleting substances, microbiological changes in river flow patterns sediment transport regimes. Water index (WQI) an important dynamic attribute characterization quality. WQ scores do not reflect actual condition water We proposed a new forecast scheme for based on following qualitative classes very good (0-25), (26-50), poor (51-75), (76-100) extremely polluted/non-potable (>100). forecasting using Artificial Intelligence (AI) meaningful method protecting public because its possibility to provide early warning regarding harmful pollutants. main objective present study WQI time series data physical, chemical status parameters associated scores. Cascade-forward network (CFN) models, along Radial Basis Function Network (RBF) as benchmark model, were developed from 2011 2017 forecasts produced period 2018-2019 at all sites. nineteen input features represent initial dataset. Moreover, Random Forest (RF) algorithm refines dataset selecting eight considered most relevant. Both datasets are employed constructing predictive models. According results appraisal, CFN models better outcomes (MSE = 0.083/0,319 R-value 0.940/0.911 quarter I/quarter IV) than RBF In addition, show that both could be effective predicting when relevant used variables. Also, CFNs accurate short-term curves which reproduce first fourth quarters (the cold season). second third presented slightly lower accuracy. reported clearly demonstrate successfully they may learn historic determine nonlinear relationships between output

Language: Английский

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Modeling, challenges, and strategies for understanding impacts of climate extremes (droughts and floods) on water quality in Asia: A review

Environmental Research, Journal Year: 2023, Volume and Issue: 225, P. 115617 - 115617

Published: March 4, 2023

The increasing frequency and intensity of extreme climate events are among the most expected recognized consequences change. Prediction water quality parameters becomes more challenging with these extremes since is strongly related to hydro-meteorological conditions particularly sensitive evidence linking influence factors on provides insights into future climatic extremes. Despite recent breakthroughs in modeling evaluations change's impact quality, informed methodologies remain restricted. This review aims summarize causal mechanisms across considering Asian methods associated extremes, such as floods droughts. In this review, we (1) identify current scientific approaches prediction context flood drought assessment, (2) discuss challenges impediments, (3) propose potential solutions improve understanding mitigate their negative impacts. study emphasizes that one crucial step toward enhancing our aquatic ecosystems by comprehending connections between through collective efforts. indices indicators were demonstrated better understand link for a selected watershed basin.

Language: Английский

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Artificial intelligence in wastewater treatment: A data-driven analysis of status and trends

Chemosphere, Journal Year: 2023, Volume and Issue: 336, P. 139163 - 139163

Published: June 7, 2023

Language: Английский

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