Evaluating the Performance of Ce-Qual-W2 Sediment Diagenesis Model DOI
Manuel Almeida,

Pedro Coelho

Published: Jan. 1, 2024

Language: Английский

Real-time, reagent-free total phosphorus soft sensor based on frequency-enhanced decomposed transformer model DOI
Weilin Guo, Yizhang Wen,

Minghuan Liu

et al.

Measurement, Journal Year: 2025, Volume and Issue: unknown, P. 117509 - 117509

Published: April 1, 2025

Language: Английский

Citations

0
Information extraction of seasonal dissolved oxygen in urban water bodies based on machine learning using sentinel-2 imagery: An open access application in Baiyangdian Lake DOI Creative Commons
Leilei Shi, Chen Gao, Tuo Wang

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: 82, P. 102782 - 102782

Published: Aug. 23, 2024

Water bodies are crucial components of urban ecology. The development rapid and timely water-quality assessment tools using easily measured variables is essential for the health management water bodies. In this study, we focused on dissolved oxygen (DO) Baiyangdian Lake 251 sets empirically quality data corresponding Sentinel-2 satellite images. Nine machine learning algorithms were then used to develop a detection algorithm spatial distribution DO concentration in Lake. This study successfully applied these methods invert during spring, summer, autumn. results indicated that extra tree regression (ETR) provided most accurate stable inverting among nine methods. contrast, AdaBoost (ABR), Bayesian ridge (BRR), support vector machines (SVM) exhibit relatively poor performance lack sensitivity concentrations. Moreover, ranged from approximately 0 12 mg/L, with notable spatiotemporal variations. highest overall was observed particularly southern region. significantly decreased summer compared higher values southwestern area lower northern reached its lowest value autumn, slightly estimation inversion concentrations By introducing comparing performances commonly models, achieved, thereby overcoming limitations traditional monitoring inversion. It not only intuitively explained temporal variation patterns but also laid foundation further in-depth exploration interactions between other parameters.

Language: Английский

Citations

2
Advanced machine learning schemes for prediction CO2 flux based experimental approach in underground coal fire areas DOI Creative Commons
Yongjun Wang,

Mengxiong Guo,

Hung Vo Thanh

et al.

Journal of Advanced Research, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Underground coal fires pose significant environmental and health risks due to releasing CO

Language: Английский

Citations

2
Global Spatial Projections of Forest Soil Respiration and Associated Uncertainties DOI Open Access

Lingxia Feng,

Junjie Jiang, Junguo Hu

et al.

Forests, Journal Year: 2024, Volume and Issue: 15(11), P. 1982 - 1982

Published: Nov. 10, 2024

The accurate prediction of global forest soil respiration (Rs) is critical for climate change research. Rs consists autotrophic (Ra) and heterotrophic (Rh) respiration, which respond differently to environmental factors. Predicting as a single flux can be biased; therefore, Ra Rh should predicted separately improve accuracy. In this study, we used the SRDB_V5 database random model analyze uncertainty in predicting using (SGM) Ra/Rh specific categorical (SCM) spatial dynamics distribution pattern Ra, Rh, future under two different patterns. results show that higher tropical inland climatic conditions, while fluctuates less than Rs. addition, SCM predictions better capture key factors are more consistent with actual data. SSP585 (high emissions) scenario, projected increase by 19.59 percent, SSP126 (low increases only 3.76 percent over 80 years, underlines need projections.

Language: Английский

Citations

1
Advanced data augmentation techniques coupled with enhanced particle swarm optimization for predicting total phosphorus concentrations in limited transmission spectra samples: A case study on the Yangtze River DOI
Guohao Zhang, Cailing Wang, Hongwei Wang

et al.

Journal of Water Process Engineering, Journal Year: 2024, Volume and Issue: 68, P. 106547 - 106547

Published: Nov. 15, 2024

Language: Английский

Citations

0
Probabilistic mapping of imbalanced data for groundwater contamination using classification algorithms: Performance and reliability DOI
Yang Qiu, Aiguo Zhou, Hanxiang Xiong

et al.

Groundwater for Sustainable Development, Journal Year: 2024, Volume and Issue: 28, P. 101393 - 101393

Published: Dec. 11, 2024

Language: Английский

Citations

0
Evaluating the Performance of Ce-Qual-W2 Sediment Diagenesis Model DOI
Manuel Almeida,

Pedro Coelho

Published: Jan. 1, 2024

Language: Английский

Citations

0