Results 31 to 40 of about 16,649 (216)

Effectiveness of Variable Selection Methods for Machine Learning and Classical Statistical Models

Quantitative Methods in Economics
In line with new international financial supervision directives (IFRS9), banks should look at a new set of analytical tools, such as machine learning. The introduction of these methods into banking practice requires reformulation of business goals, both
Urszula Grzybowska, Marek Karwański
doaj   +1 more source

Climatic Drivers of Plant Species Distributions Across Spatial Grains in Southern Africa Tropical Forests

Frontiers in Forests and Global Change, 2019
Understanding the importance of climate in determining species distribution and how it might change as a function of spatial grain size is a vital issue for species distribution modeling (SDM), yet it is often not accounted for in models and has not been
Boipelo Tshwene-Mauchaza, Jesús Aguirre-Gutiérrez, Jesús Aguirre-Gutiérrez   +2 more
doaj   +1 more source

Non-Intrusive Identification of Loads by Random Forest and Fireworks Optimization

IEEE Access, 2020
The control of expenses related to electricity has been showing significant growth, especially in residential environments. Monitoring of electrical loads that are turning on and off from home are often performed using smart plugs, providing to the ...
Paulo Ricardo Zambelli Taveira, Carlos Henrique Valerio De Moraes, Germano Lambert-Torres   +2 more
doaj   +1 more source

Learning variable importance to guide recombination [PDF]

2016 IEEE Symposium Series on Computational Intelligence (SSCI), 2016
In evolutionary multi-objective optimization, variation operators are crucially important to produce improving solutions, hence leading the search towards the most promising regions of the solution space. In this paper, we propose to use a machine learning modeling technique, namely random forest, in order to estimate, at each iteration in the course ...
Sagawa, Miyako, Aguirre, Hernan, Daolio, Fabio, Liefooghe, Arnaud, Derbel, Bilel, Verel, Sébastien, Tanaka, Kiyoshi   +6 more
openaire   +2 more sources

Impacts of Soil Properties, Topography, and Environmental Features on Soil Water Holding Capacities (SWHCs) and Their Interrelationships

Land, 2021
Soil water holding capacities (SWHCs) are among the most important factors for understanding the water cycle in forested catchments because they control available plant water that supports evapotranspiration.
Hyunje Yang, Hyeonju Yoo, Honggeun Lim, Jaehoon Kim, Hyung Tae Choi   +4 more
doaj   +1 more source

A Novel Traffic Speed Prediction for Road Weaving Sections: Incorporating Traffic Flow Characteristics

Promet (Zagreb)
Weaving sections on roads are crucial areas with high concentrations of mandatory lane changes, which can increase the likelihood of traffic accidents.
Yuming ZHOU, Min ZHANG, Chi ZHANG, Zilong XIE, Bo WANG   +4 more
doaj   +1 more source

Retrieval and Mapping of Soil Organic Carbon Using Sentinel-2A Spectral Images from Bare Cropland in Autumn

Remote Sensing, 2021
Soil is the largest carbon reservoir on the terrestrial surface. Soil organic carbon (SOC) not only regulates global climate change, but also indicates soil fertility level in croplands.
Ke Wang, Yanbing Qi, Wenjing Guo, Jielin Zhang, Qingrui Chang   +4 more
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Health‐Related Social Needs in Children With Sickle Cell Disease Are Associated With Worse Health‐Related Quality of Life

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Children with sickle cell disease (SCD) face multiple acute and chronic medical complications that may impact their quality of life as reported by patients themselves. Health‐related social needs (HRSNs), such as food and housing insecurity, are common in people with SCD, but the association between HRSNs and patient‐reported ...
Sarah J. Marks, Molly Sonenklar, Cerelia Donald, Cecelia Valrie, Wally Smith, India Sisler   +5 more
wiley   +1 more source

Partially fixed bayesian additive regression trees

Statistical Theory and Related Fields
Bayesian Additive Regression Trees (BART) is a widely popular nonparametric regression model known for its accurate prediction capabilities. In certain situations, there is knowledge suggesting the existence of certain dominant variables.
Hao Ran, Yang Bai
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Multi‐Model Prediction of West Nile Virus Neuroinvasive Disease With Machine Learning for Identification of Important Regional Climatic Drivers

GeoHealth, 2023
West Nile virus (WNV) is the leading cause of mosquito‐borne illness in the continental United States (CONUS). Spatial heterogeneity in historical incidence, environmental factors, and complex ecology make prediction of spatiotemporal variation in WNV ...
Karen M. Holcomb, J. Erin Staples, Randall J. Nett, Charles B. Beard, Lyle R. Petersen, Stanley G. Benjamin, Benjamin W. Green, Hunter Jones, Michael A. Johansson   +8 more
doaj   +1 more source