Results 81 to 90 of about 28,744 (310)

Understanding Egg Price Volatility and Policy Implications in the U.S. With Machine Learning

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT Eggs are an inexpensive and sustainable source of proteins, but volatility in the U.S. egg prices has intensified in recent years, raising concerns over food affordability and market stability. This study examines the drivers of U.S. egg price dynamics over 2004–2025 using a two‐stage framework that combines LASSO‐based variable selection with
Xuemei Zhao, Simon Meister, Lucie Maruejols, Xiaohua Yu   +3 more
wiley   +1 more source

Sparse Regularization in Marketing and Economics

, 2018
Sparse alpha-norm regularization has many data-rich applications in Marketing and Economics. Alpha-norm, in contrast to lasso and ridge regularization, jumps to a sparse solution.
Feng, Guanhao, Polson, Nicholas, Wang, Yuexi, Xu, Jianeng   +3 more
core   +1 more source

Foreign labor, peer‐networking and agricultural efficiency in the Italian dairy sector

Agribusiness, EarlyView.
Abstract While the presence of immigrants in the agricultural sector is widely acknowledged, the empirical evidence on its economic consequences is lacking, especially from a microeconomic perspective. Using the Farm Accountancy Data Network panel data for Italian dairy farms in the period 2008–2018, the present study investigates the relationship ...
Federico Antonioli, Simone Severini, Mauro Vigani   +2 more
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

From satellites to yield: causal modeling of paddy rice production using sparse regression and dynamic remote sensing [PDF]

Scientia Agricola
: This study presents a novel approach that combines agricultural census data with remotely sensed time series to develop accurate predictive models for paddy rice yield across the different regions of Peru.
Rita Rocio Guzman-Lopez, Luis Huamanchumo de la Cuba, Kevin Anthony Fernandez Molina, Oscar Diego Fernando Cutipa-Luque, Yhon Tiahuallpa Yucra, Helder Rojas   +5 more
doaj   +2 more sources

Fast Convergence Rate of Multiple Kernel Learning with Elastic-net Regularization [PDF]

, 2011
We investigate the learning rate of multiple kernel leaning (MKL) with elastic-net regularization, which consists of an $\ell_1$-regularizer for inducing the sparsity and an $\ell_2$-regularizer for controlling the smoothness.
Sugiyama, Masashi, Suzuki, Taiji, Tomioka, Ryota   +2 more
core  

Variable selection and regression analysis for graph-structured covariates with an application to genomics

, 2010
Graphs and networks are common ways of depicting biological information. In biology, many different biological processes are represented by graphs, such as regulatory networks, metabolic pathways and protein--protein interaction networks.
Li, Caiyan, Li, Hongzhe
core   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source