The Citing articles tool gives a list of articles citing the current article. The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
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Inverse modeling of untethered electromagnetic actuators using machine learning
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What, where, and when: Spatial-temporal distribution of macro-litter on the seafloor of the western and central Mediterranean sea
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Public debt forecasts and machine learning: the Italian case
Digital assessments of soil organic carbon storage using digital maps provided by static and dynamic environmental covariates
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Distinguishing Tree Species from In Situ Hyperspectral and Temporal Measurements through Ensemble Statistical Learning
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Uncovering the effects of Urmia Lake desiccation on soil chemical ripening using advanced mapping techniques
Predicting spatial distribution of stable isotopes in precipitation by classical geostatistical- and machine learning methods
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Improving Sampling Probability Definitions with Predictive Algorithms
Random Forest Algorithm for the Strength Prediction of Geopolymer Stabilized Clayey Soil
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Modeling the Combined Effect of Fulvic Acid, Effective Microorganisms and Micro-Carbon on Olive Yield
Waleed Mohammad Elhanafy F, Younes Mohammad Rashad and Omar Maghawry Ibrahim Asian Journal of Plant Sciences 22(2) 394 (2023) https://doi.org/10.3923/ajps.2023.394.405
Tile-Based Random Forest Analysis for Analyte Discovery in Balanced and Unbalanced GC × GC-TOFMS Data Sets
Meriem Gaida, Caitlin N. Cain, Robert E. Synovec, Jean-François Focant and Pierre-Hugues Stefanuto Analytical Chemistry 95(36) 13519 (2023) https://doi.org/10.1021/acs.analchem.3c01872
Application of random forest (RF) for flood levels prediction in Lower Ogun Basin, Nigeria
Ore genesis of the Laguhe Au deposit, West Qinling, China: Evidence from sulfide geochemistry and machine learning
Feifan Xu, Fan Yang, Emmanuel John M. Carranza, Kangning Li, Shuai Zhang, Qingyan Tang and Dengbang Li Ore Geology Reviews 163 105767 (2023) https://doi.org/10.1016/j.oregeorev.2023.105767
Analysis of the Frictional Performance of AW-5251 Aluminium Alloy Sheets Using the Random Forest Machine Learning Algorithm and Multilayer Perceptron
Tomasz Trzepieciński, Sherwan Mohammed Najm, Omar Maghawry Ibrahim and Marek Kowalik Materials 16(15) 5207 (2023) https://doi.org/10.3390/ma16155207
Chemical Descriptors for a Large-Scale Study on Drop-Weight Impact Sensitivity of High Explosives
Frank W. Marrs, Jack V. Davis, Alexandra C. Burch, et al. Journal of Chemical Information and Modeling 63(3) 753 (2023) https://doi.org/10.1021/acs.jcim.2c01154
Effects of stopping criterion on the growth of trees in regression random forests
Aryana Arsham, Philip Rosenberg and Mark Little The New England Journal of Statistics in Data Science 46 (2023) https://doi.org/10.51387/22-NEJSDS5
AI-based identification of therapeutic agents targeting GPCRs: introducing ligand type classifiers and systems biology
Jonas Goßen, Rui Pedro Ribeiro, Dirk Bier, Bernd Neumaier, Paolo Carloni, Alejandro Giorgetti and Giulia Rossetti Chemical Science 14(32) 8651 (2023) https://doi.org/10.1039/D3SC02352D
Tropical cyclone full track simulation in the western North Pacific based on random forests
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Everybody is Populist to Some Extent: Measuring Parties' Populist Rhetoric with Machine Learning Tools.
A Machine Learning-based Cloud Detection Algorithm for the Himawari-8 Spectral Image
Chao Liu, Shu Yang, Di Di, et al. Advances in Atmospheric Sciences 39(12) 1994 (2022) https://doi.org/10.1007/s00376-021-0366-x
Pietro Mastro, Domenico Cimini, Filomena Romano, Elisabetta Ricciardelli, Francesco Di Paola, Guido Masiello, Carmine Serio, Adolfo Comerón, Evgueni I. Kassianov, Klaus Schäfer, Richard H. Picard, Konradin Weber and Upendra N. Singh 29 (2022) https://doi.org/10.1117/12.2642874
Moisés R. Santos, Douglas D. C. Braz, André C. P. L. F. Carvalho, Renato Tinós, Marcos B. S. Paula, Gabriel Doretto, Ewerton Guarnier, Donato Silva Filho, Danilo Y. Suiama, Lorena E. Ferreira and José E. Carmo Júnior 1 (2022) https://doi.org/10.1109/LA-CCI54402.2022.9981846
Mapping soil erodibility in southeast China at 250 m resolution: Using environmental variables and random forest regression with limited samples
Nonlinear Effects of the Neighborhood Environments on Residents’ Mental Health
Lin Zhang, Suhong Zhou, Lanlan Qi and Yue Deng International Journal of Environmental Research and Public Health 19(24) 16602 (2022) https://doi.org/10.3390/ijerph192416602
Estimation of Eucalyptus productivity using efficient artificial neural network
Ricardo Rodrigues de Oliveira Neto, Helio Garcia Leite, José Marinaldo Gleriani and Bogdan M. Strimbu European Journal of Forest Research 141(1) 129 (2022) https://doi.org/10.1007/s10342-021-01431-7
Improving nonconformity responsibility decisions: a semi-automated model based on CRISP-DM
IoT-based platform for automated IEQ spatio-temporal analysis in buildings using machine learning techniques
Francisco Troncoso-Pastoriza, Miguel Martínez-Comesaña, Ana Ogando-Martínez, Javier López-Gómez, Pablo Eguía-Oller and Lara Febrero-Garrido Automation in Construction 139 104261 (2022) https://doi.org/10.1016/j.autcon.2022.104261
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Exploiting limited players’ behavioral data to predict churn in gamification
Mobile‐aided screening system for proliferative diabetic retinopathy
Rahma Boukadida, Yaroub Elloumi, Mohamed Akil and Mohamed Hedi Bedoui International Journal of Imaging Systems and Technology 31(3) 1638 (2021) https://doi.org/10.1002/ima.22547
Muscle Synergy of Lower Limb Motion in Subjects with and without Knee Pathology
Mapping and Quantification of the Dwarf Eelgrass Zostera noltei Using a Random Forest Algorithm on a SPOT 7 Satellite Image
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Short-Term Forecasting of Household Water Demand in the UK Using an Interpretable Machine Learning Approach
Hiu Fai Lee and Ming Jiang Communications in Computer and Information Science, Neural Computing for Advanced Applications 1449 211 (2021) https://doi.org/10.1007/978-981-16-5188-5_16
Assessing the geographic specificity of pH prediction by classification and regression trees
Sonoma County Complex Fires of 2017: Remote sensing data and modeling to support ecosystem and community resiliency
Kass Green, Mark Tukman, Dylan Loudon, et al. California Fish and Wildlife Journal 106(Fire Special Issue) (2020) https://doi.org/10.51492/cfwj.firesi.1
Prediction of sorption enhanced steam methane reforming products from machine learning based soft-sensor models
Machine Learning Methods for Classification of the Green Infrastructure in City Areas
Nikola Kranjčić, Damir Medak, Robert Župan and Milan Rezo ISPRS International Journal of Geo-Information 8(10) 463 (2019) https://doi.org/10.3390/ijgi8100463
Hyperparameters and tuning strategies for random forest
Philipp Probst, Marvin N. Wright and Anne‐Laure Boulesteix WIREs Data Mining and Knowledge Discovery 9(3) (2019) https://doi.org/10.1002/widm.1301
Learning-Based Colorization of Grayscale Aerial Images Using Random Forest Regression