Cover Image

A comparison between geostatistical and machine learning models for spatio-temporal prediction of PM2.5 data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mohamed, Zeinab, Gong, Wenlong
Format:	Preprint
Published:	2025
Subjects:	Applications Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Foundation for unbiased cross-validation of spatio-temporal models for species distribution modeling
by: Koldasbayeva, Diana, et al.
Published: (2025)

A nonstationary spatial model of PM2.5 with localized transfer learning from numerical model output
by: Gong, Wenlong, et al.
Published: (2025)

Causal machine learning for predicting treatment outcomes
by: Feuerriegel, Stefan, et al.
Published: (2024)

Ground-Level Near Real-Time Modeling for PM2.5 Pollution Prediction
by: Fox, Zachary R., et al.
Published: (2026)

Variable importance measure for spatial machine learning models with application to air pollution exposure prediction
by: Cheng, Si, et al.
Published: (2024)

Applications of machine learning to predict seasonal precipitation for East Africa
by: Scheuerer, Michael, et al.
Published: (2024)

Stability of clinical prediction models developed using statistical or machine learning methods
by: Riley, Richard D, et al.
Published: (2022)

Predicting fall risk in older adults: A machine learning comparison of accelerometric and non-accelerometric factors
by: González-Castro, Ana, et al.
Published: (2025)

A comparative analysis of machine learning algorithms for predicting probabilities of default
by: Cristescu, Adrian Iulian, et al.
Published: (2025)

Error-controlled non-additive interaction discovery in machine learning models
by: Chen, Winston, et al.
Published: (2024)

Classification problem in liability insurance using machine learning models: a comparative study
by: Qazvini, Marjan
Published: (2024)

Uncertainty estimation of machine learning spatial precipitation predictions from satellite data
by: Papacharalampous, Georgia, et al.
Published: (2023)

Tackling water table depth modeling via machine learning: From proxy observations to verifiability
by: Janssen, Joseph, et al.
Published: (2024)

Partially stochastic deep learning with uncertainty quantification for model predictive heating control
by: Hannula, Emma, et al.
Published: (2025)

Are machine learning interpretations reliable? A stability study on global interpretations
by: Gan, Luqin, et al.
Published: (2025)

A machine learning approach to predict university enrolment choices through students' high school background in Italy
by: Priulla, Andrea, et al.
Published: (2024)

Probabilistic intraday electricity price forecasting using generative machine learning
by: Chen, Jieyu, et al.
Published: (2025)

A meta-analysis on the performance of machine-learning based language models for sentiment analysis
by: Rohde, Elena, et al.
Published: (2025)

A generative machine learning model for designing metal hydrides applied to hydrogen storage
by: Liu, Xiyuan, et al.
Published: (2026)

A two-step machine learning approach to statistical post-processing of weather forecasts for power generation
by: Baran, Ágnes, et al.
Published: (2022)

Analysis of ELSA COVID-19 Substudy response rate using machine learning algorithms
by: Qazvini, Marjan
Published: (2024)

Spatio-temporal modelling of electric vehicle charging demand
by: Bouaachra, Kaoutar, et al.
Published: (2026)

Detecting Urban PM$_{2.5}$ Hotspots with Mobile Sensing and Gaussian Process Regression
by: Perry, Niál, et al.
Published: (2025)

The temporal overfitting problem with applications in wind power curve modeling
by: Prakash, Abhinav, et al.
Published: (2020)

Spatio-temporal fusion of reanalysis and in situ data for censored threshold exceedances of PM2.5
by: Cuba, M. Daniela, et al.
Published: (2025)

Ensemble data assimilation to diagnose AI-based weather prediction model: A case with ClimaX version 0.3.1
by: Kotsuki, Shunji, et al.
Published: (2024)

A weighted-likelihood framework for class imbalance in Bayesian prediction models
by: Lazic, Stanley E.
Published: (2025)

Diagnosis-based mortality prediction for intensive care unit patients via transfer learning
by: Xu, Mengqi, et al.
Published: (2025)

Predicting loss-of-function impact of genetic mutations: a machine learning approach
by: Kaur, Arshmeet, et al.
Published: (2024)

An empirical comparison of some outlier detection methods with longitudinal data
by: D'Orazio, Marcello
Published: (2025)

Rashomon perspective for measuring uncertainty in the survival predictive maintenance models
by: Yardimci, Yigitcan, et al.
Published: (2025)

Beyond Beats: A Recipe to Song Popularity? A machine learning approach
by: Sebastian, Niklas, et al.
Published: (2024)

Logistic regression models for patient-level prediction based on massive observational data: Do we need all data?
by: John, Luis H., et al.
Published: (2020)

Meta-models for transfer learning in source localisation
by: Bull, Lawrence A., et al.
Published: (2023)

Uncertainty quantification in automated valuation models with spatially weighted conformal prediction
by: Hjort, Anders, et al.
Published: (2023)

Personalised dynamic super learning: an application in predicting hemodiafiltration convection volumes
by: Chatton, Arthur, et al.
Published: (2023)

Online model learning with data-assimilated reservoir computers
by: Nóvoa, Andrea, et al.
Published: (2025)

Multivariate disaggregation modeling of air pollutants: a case-study of PM2.5, PM10 and ozone prediction in Portugal and Italy
by: Avellaneda, Fernando Rodriguez, et al.
Published: (2025)

Correcting heterogeneous diagnostic bias when developing clinical prediction models using causal hidden Markov models
by: Benitez-Aurioles, Jose, et al.
Published: (2026)

An unsupervised learning approach to evaluate questionnaire data -- what one can learn from violations of measurement invariance
by: Hahn-Klimroth, Max, et al.
Published: (2023)