Mostrando 5 resultados de: 5
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Advances in Intelligent Systems and Computing(2)
Applied Sciences (Switzerland)(1)
Frontiers in Big Data(1)
WIT Transactions on Ecology and the Environment(1)
Deep Learning Approach for Assessing Air Quality During COVID-19 Lockdown in Quito
ArticleAbstract: Weather Normalized Models (WNMs) are modeling methods used for assessing air contaminants under a buPalabras claves:air pollution, covid-19, data-driven modeling and optimization, deep learning - artificial neural network (DL-ANN), Machine learningAutores:Chau P.N., Rasa Zalakeviciute, Rybarczyk Y.P., Thomas I.Fuentes:googlescopusEvaluation of smart phone open source applications for air pollution
Conference ObjectAbstract: Global industrialization, urbanization and technological development have been rapidly changing thePalabras claves:air pollution, Evaluation, Mobile ApplicationsAutores:Jorge Luis Pérez Medina, Katiuska Alexandrino, Patricia Acosta-Vargas, Rasa Zalakeviciute, Wilmar HernandezFuentes:googlescopusENSEMBLE DEEP LEARNING FOR CLASSIFICATION OF POLLUTION PEAKS
Conference ObjectAbstract: The concentration peaks of atmospheric pollutants are the most challenging and important phenomena iPalabras claves:air pollution forecasting, data-driven modelling, deep learning, Machine learningAutores:Chau P.N., Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:googlescopusHeuristic method of evaluating accessibility of mobile in selected applications for air quality monitoring
Conference ObjectAbstract: At present, advances in technology, the use of smartphones and access to the Internet pose significaPalabras claves:accessibility, Air, Applications, Evaluation, Heuristic method, Mobile, Monitoring, Quality, WCAG 2.1Autores:Jorge Luis Pérez Medina, Luis Salvador-Ullauri, Patricia Acosta-Vargas, Rasa Zalakeviciute, Wilmar HernandezFuentes:scopusMachine learning approaches for outdoor air quality modelling: A systematic review
ReviewAbstract: Current studies show that traditional deterministic models tend to struggle to capture the non-lineaPalabras claves:Atmospheric pollution, Data Mining, Multiple correspondence analysis, pbkp_redictive modelsAutores:Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:googlescopus