Imagen de Portada

Identification of socioeconomic factors influencing global food price security using machine learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Shan, Shan
Formato:	Preprint
Publicado:	2024
Materias:	Applications
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

Certification of MPC-based zonal controller security properties using accuracy-aware machine learning proxies
por: Houdouin, Pierre, et al.
Publicado: (2024)

A representation-learning approach for insurance pricing with images
por: Blier-Wong, Christopher, et al.
Publicado: (2023)

Traffic noise assessment in urban Bulgaria using explainable machine learning
por: Helbic, Marco, et al.
Publicado: (2025)

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

Assessing variable importance in survival analysis using machine learning
por: Wolock, Charles J., et al.
Publicado: (2023)

Real-time small area estimation of food security in Zimbabwe: integrating mobile-phone and face-to-face surveys using joint multilevel regression and poststratification
por: Ishida, Sahoko, et al.
Publicado: (2025)

Probabilistic storyline attribution using machine learning
por: Loer, Frieder, et al.
Publicado: (2026)

Age-Dependent Heterogeneity in the Association Between Physical Activity and Mental Distress: A Causal Machine Learning Analysis of 3.2 Million U.S. Adults
por: Shan, Yuan
Publicado: (2026)

Validity in machine learning for extreme event attribution
por: Chou, Cassandra C., et al.
Publicado: (2025)

Analysis of points outcome in ATP Grand Slam Tennis using big data and machine learning
por: Illum, Martin, et al.
Publicado: (2025)

Stochastic modeling of particle structures in spray fluidized bed agglomeration using methods from machine learning
por: Fuchs, Lukas, et al.
Publicado: (2025)

Optimal day-ahead offering strategy for large producers based on market price response learning
por: Alcántara, António, et al.
Publicado: (2022)

On factors influencing consumer preference in pipeline stages: an experiment
por: Pramanik, Paramahansa, et al.
Publicado: (2025)

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

The contribution of machine learning to the prevention of burnout among healthcare workers in Morocco
por: Eddaou, Mohammed
Publicado: (2025)

Integrating socioeconomic and geographic data to enhance infectious disease prediction in Brazilian cities
por: Lober, Luiza, et al.
Publicado: (2024)

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

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

Deciphering the influence of demographic factors on the treatment of pediatric patients in the emergency department
por: Coggan, Helena, et al.
Publicado: (2025)

Surface temperature extremes produced by huge machine learning hindcasts of summer 2023
por: Risser, Mark, et al.
Publicado: (2026)

A causal machine learning approach to disentangling the pressure-satisfaction pathways in depression
por: Nan, Zhaojin
Publicado: (2025)

Human Limits in Machine Learning: Prediction of Plant Phenotypes Using Soil Microbiome Data
por: Aghdam, Rosa, et al.
Publicado: (2023)

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

Double machine learning to estimate the effects of multiple treatments and their interactions
por: Xiang, Qingyan, et al.
Publicado: (2025)

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

Bayesian Record Linkage with Variables in One File
por: Kamat, Gauri, et al.
Publicado: (2023)

Adaptive probabilistic forecasting of French electricity spot prices
por: Dutot, Grégoire, et al.
Publicado: (2024)

Multifractal behavior of price changes in the Green Bonds funds
por: Barbosa, Wenderson Gomes, et al.
Publicado: (2025)

Assessing the influence of social media feedback on traveler's future trip-planning behavior: A multi-model machine learning approach
por: Mukherjee, Sayantan, et al.
Publicado: (2025)

Urban mobility and learning: analyzing the influence of commuting time on students' GPA at Politecnico di Milano
por: Burzacchi, Arianna, et al.
Publicado: (2024)

Using spatial extreme-value theory with machine learning to model and understand spatially compounding weather extremes
por: Koh, Jonathan, et al.
Publicado: (2024)

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

Expectile regression averaging method for probabilistic forecasting of electricity prices
por: Janczura, Joanna
Publicado: (2024)

Do machine learning methods lead to similar individualized treatment rules? A comparison study on real data
por: Bouvier, Florie, et al.
Publicado: (2023)

Waiting for Dabo: A machine learning model for predicting Power 4 college football coaching hire success
por: Schuckers, Michael, et al.
Publicado: (2025)

Precrop Payoffs: Causal machine learning reveals large but variable yield benefits of crop rotation in major breadbaskets
por: Kluger, Dan M., et al.
Publicado: (2025)

How to identify earth pressures on in-service tunnel linings: Insights from Bayesian inversion to address non-uniqueness
por: Tian, Zhiyao, et al.
Publicado: (2024)

Density correction for multivariate spatial fields of global climate model output using deep learning
por: Majumder, Reetam, et al.
Publicado: (2024)

Regularization for electricity price forecasting
por: Uniejewski, Bartosz
Publicado: (2024)