Exploring the Potential of the Machine Learning Techniques in the Water Quality Assessment: A Review of Applications and Performance DOI
Fausto Pedro Garcı́a Márquez, Ali Hussein Shuaa Al-taie, Yahya Zakur

et al.

Lecture notes in networks and systems, Journal Year: 2024, Volume and Issue: unknown, P. 626 - 639

Published: Jan. 1, 2024

Language: Английский

Predictive Modeling of Urban Lake Water Quality Using Machine Learning: A 20-Year Study DOI Creative Commons
Tymoteusz Miller, Irmina Durlik,

Adrianna Krzemińska

et al.

Applied Sciences, Journal Year: 2023, Volume and Issue: 13(20), P. 11217 - 11217

Published: Oct. 12, 2023

Water-quality monitoring in urban lakes is of paramount importance due to the direct implications for ecosystem health and human well-being. This study presents a novel approach predicting Water Quality Index (WQI) an lake over span two decades. Leveraging power Machine Learning (ML) algorithms, we developed models that not only predict, but also provide insights into, intricate relationships between various water-quality parameters. Our findings indicate significant potential using ML techniques, especially when dealing with complex environmental datasets. The methods employed this are grounded both statistical computational principles, ensuring robustness reliability their predictions. significance our research lies its ability timely accurate forecasts, aiding proactive water-management strategies. Furthermore, delve into explanations behind success models, emphasizing capability capture non-linear patterns data, which traditional might overlook.

Language: Английский

Citations

10

Measuring Urban Green Space Exposure Based on Street View Images and Machine Learning DOI Open Access
Tianlin Zhang, Lei Wang,

Yike Hu

et al.

Forests, Journal Year: 2024, Volume and Issue: 15(4), P. 655 - 655

Published: April 3, 2024

Exposure to green spaces (GSs) has been perceived as a natural and sustainable solution urban challenges, playing vital role in rapid urbanization. Previous studies, due their lack of direct spatial alignment attention human-scale perspective, struggled comprehensively measure GS exposure. To address this gap, our study introduces novel exposure assessment framework, employing machine learning street view images. We conducted large-scale, fine-grained empirical focused on downtown Shanghai. Our findings indicate pronounced hierarchical structure the distribution exposure, which initially increases subsequently decreases one moves outward from city center. Further, both micro macro perspectives, we employed structural equation modeling Geodetector investigate impact built environment results highlight that maintaining an appropriate level architectural density, enhancing combination sidewalks with GSs, emphasizing diversity regional characteristics, avoiding excessive concentration functions are effective approaches for increasing promoting human wellbeing. offers scientific insights planners administrators, holding significant implications achieving development.

Language: Английский

Citations

3

Spatio-Temporal Variation in Landforms and Surface Urban Heat Island in Riverine Megacity DOI Open Access

Namita Gorai,

Jatisankar Bandyopadhyay, Bijay Halder

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(8), P. 3383 - 3383

Published: April 18, 2024

Rapid urbanization and changing climatic procedures can activate the present surface urban heat island (SUHI) effect. An SUHI was considered by temperature alterations among rural surroundings. The zones were frequently warmer than regions because of population pressure, urbanization, vegetation insufficiency, industrialization, transportation systems. This investigation analyses Surface-UHI influence in Kolkata Municipal Corporation (KMC), India. Growing land (LST) may cause an impact ecological conditions regions. thermal field variation index (UTFVI) served as a qualitative quantitative barrier to susceptibility. maximum likelihood approach used conjunction with supervised classification techniques identify variations use cover (LULC) over chosen year. outcomes designated reduction around 1354.86 Ha, 653.31 2286.9 434.16 Ha for vegetation, bare land, grassland, water bodies, correspondingly. Temporarily, from years 1991–2021, built-up area increased 4729.23 Ha. highest LST 7.72 °C, while lowest 5.81 °C 1991 2021. showed negative link, according correlation analyses; however, experimentally measured positive correlation. inquiry will compel administration, planners, stakeholders observe humanistic activities thus confirm sustainable expansion.

Language: Английский

Citations

3

Impact of artificial intelligence for the recycling of organic waste DOI
Malik Adil Nawaz, Deepak M. Kasote

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 347 - 362

Published: Jan. 1, 2025

Language: Английский

Citations

0

Improving deep learning-based streamflow forecasting under trend varying conditions through evaluation of new wavelet preprocessing technique DOI
Mohammad Reza M. Behbahani,

Maryam Mazarei,

Amvrossios C. Bagtzoglou

et al.

Stochastic Environmental Research and Risk Assessment, Journal Year: 2024, Volume and Issue: 38(10), P. 3963 - 3984

Published: Aug. 5, 2024

Language: Английский

Citations

2

Assessing sustainability of Chiang Mai urban development DOI Creative Commons

Wiwat Pongruengkiat,

Korrakot Yaibuathet Tippayawong, Pruk Aggarangsi

et al.

Discover Sustainability, Journal Year: 2023, Volume and Issue: 4(1)

Published: Dec. 11, 2023

Abstract Sustainable urban development is an increasingly important concept as cities around the world continue to grow and face challenges related urbanization, including environmental degradation, social inequality, economic instability. Chiang Mai a rapidly growing city in Thailand that steers towards sustainability. In this work, we examine state of sustainable by analyzing various indicators, transportation, waste management, air quality, energy consumption. A multi-dimensional framework was used assess sustainability Mai. Our analysis suggests while has made progress some areas development, such promoting green transportation reduction consumption, there are still many be addressed, particularly pollution, water We conclude discussing implications our findings for policy makers, planners, other stakeholders interested development. This study assesses Mai’s using comprehensive set 35 indicators. It found potential but indicators require improvement. The presents guidelines prioritizing improving tourism, enhancing management research provides alternative evaluating valuable contribution field

Language: Английский

Citations

6

Diversifying natural resources for green recovery in China: Strategies and solutions DOI
Yu Liu, Yiming Li, Fan Jiang

et al.

Resources Policy, Journal Year: 2023, Volume and Issue: 88, P. 104399 - 104399

Published: Nov. 24, 2023

Language: Английский

Citations

5

Groundwater harvesting and artificial recharge site identification on upper Shilabati watershed using geospatial approaches DOI
Bijay Halder, Jatisankar Bandyopadhyay,

Sonamani Hemram

et al.

Theoretical and Applied Climatology, Journal Year: 2024, Volume and Issue: 155(6), P. 5297 - 5322

Published: April 5, 2024

Language: Английский

Citations

1

Water environment risk prediction method based on convolutional neural network-random forest DOI

Yanan Zhao,

Lili Zhang, Yue Chen

et al.

Marine Pollution Bulletin, Journal Year: 2024, Volume and Issue: 209, P. 117228 - 117228

Published: Nov. 13, 2024

Language: Английский

Citations

1

Turning trash into treasure: Exploring the potential of AI in municipal waste management - An in-depth review and future prospects DOI Creative Commons

Asmae El Jaouhari,

Ashutosh Samadhiya, Anil Kumar

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 373, P. 123658 - 123658

Published: Dec. 9, 2024

Language: Английский

Citations

1