Advanced Air Quality Forecasting Using an Enhanced Temporal Attention-Driven Graph Convolutional Long Short-Term Memory Model with Seasonal-Trend Decomposition DOI Creative Commons

Yuvaraja Boddu,

Manimaran Aridoss, Arunkumar Balakrishnan

и другие.

IEEE Access, Год журнала: 2024, Номер 12, С. 189233 - 189252

Опубликована: Янв. 1, 2024

Язык: Английский

Groundwater for drinking and sustainable agriculture and public health hazards of nitrate: developmental and sustainability implications for an arid aquifer system DOI Creative Commons
Boualem Bouselsal,

Adel Satouh,

Johnbosco C. Egbueri

и другие.

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104160 - 104160

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

5
Enhanced Prediction of Energy Dissipation Rate in Hydrofoil-Crested Stepped Spillways Using Novel Advanced Hybrid Machine Learning Models DOI Creative Commons
Ehsan Afaridegan,

Nosratollah Amanian

Results in Engineering, Год журнала: 2025, Номер unknown, С. 103985 - 103985

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

2
Geospatial digital mapping of soil organic carbon using machine learning and geostatistical methods in different land uses DOI Creative Commons
Yahya Parvizi, Shahrokh Fatehi

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 6, 2025

Improper management of soil resources leads to the destruction organic carbon (SOC) stock and, as a result, reduction quality, well accelerating process climate change through release SOC into atmosphere. This study was conducted evaluate potential different simulation models map spatial variability affected by land use in area Qarasu watershed Kermanshah province, west Iran. Map sampling points prepared using Latin hypercube method. A total 168 observation were selected and profile dug described these points. The samples taken horizon determine content laboratory. mapped kriging geostatistical method area. changes simulated multivariate analysis machine learning methods including generalized linear model (GLM), additive (LAM), cubist, random forest (RF), support vector (SVM) models. Comprehensive measurement data is utilized develop validate predictive Predictor variables included 16 topographic two vegetation, six parent material, four climatic variables. In-depth statistical analyses are proposed performance. results showed that ranged from 0.19 8.44 percent uses. spherical variogram with MAE = 0.41 best fits interpolate ordinary LAM estimated wider range (SOC 0.18–4.82%) among model. However, RF (R2 0.64 RMSE 0.58%) most accurate predicting quantity comparing other It can be used reliable predict similar semiarid regions West Asia Among predictor variables, material's intrinsic properties topography had greatest effect variability.

Язык: Английский

Процитировано

2
A Study on the water resource assets management audit for outgoing officials considering asset elements DOI
Shuqin Li,

Juqin Shen,

Fuhua Sun

и другие.

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 144931 - 144931

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

2
Enhancing Pan evaporation predictions: Accuracy and uncertainty in hybrid machine learning models DOI Creative Commons
Khabat Khosravi, Aitazaz A. Farooque, Seyed Amir Naghibi

и другие.

Ecological Informatics, Год журнала: 2024, Номер 85, С. 102933 - 102933

Опубликована: Дек. 7, 2024

Язык: Английский

Процитировано

11
Enhancing prediction of dissolved oxygen over Santa Margarita River: Long short-term memory incorporated with multi-objective observer-teacher-learner optimization DOI
Siyamak Doroudi, Yusef Kheyruri, Ahmad Sharafati

и другие.

Journal of Water Process Engineering, Год журнала: 2025, Номер 70, С. 106969 - 106969

Опубликована: Янв. 11, 2025

Язык: Английский

Процитировано

1
Evaluating empirical and machine learning approaches for reference evapotranspiration estimation using limited climatic variables in Nepal DOI Creative Commons

Erica Shrestha,

Suyog Poudyal,

Anup Ghimire

и другие.

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104254 - 104254

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1
Impact of Nutrient Dynamics on Chlorophyll-a Concentrations in Non-Interconnected Lakes: A Study in the Vellore and Chennai Region DOI Creative Commons

Mageswaran Raghul,

P. Porchelvan

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104315 - 104315

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1
Integrating piecewise and symbolic regression with remote sensing data for spatiotemporal analysis of surface water total dissolved solids in the Karun River, Iran DOI Creative Commons
Javad Zahiri, Mohammad Reza Nikoo,

Adell Moradi-Sabzkouhi

и другие.

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104159 - 104159

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Enhanced accuracy and interpretability of nitrous oxide emission prediction of wastewater treatment plants through machine learning of univariate time series: A novel approach of learning feature reconstruction DOI
Zixuan Wang, Anlei Wei, K.S. Tang

и другие.

Journal of Water Process Engineering, Год журнала: 2025, Номер 71, С. 107263 - 107263

Опубликована: Фев. 15, 2025

Язык: Английский

Процитировано

0