Machine Learning Approaches to Extreme Weather Events Forecast in Urban Areas: Challenges and Initial Results | Zendy

Fábio Porto | Zendy; Mariza Ferro | Zendy; Eduardo Ogasawara | Zendy; Thiago Moeda | Zendy; Claudio Daniel Tenorio de Barros | Zendy; Anderson Chaves da Silva | Zendy; Rocío Zorrilla | Zendy; Rafael Silva Pereira | Zendy; Rafaela Castro | Zendy; João Victor Silva | Zendy; Rebecca Salles | Zendy; Augusto J. M. da Fonseca | Zendy; Juliana Hermsdorff | Zendy; Marcelo Magalhães | Zendy; Vítor J. Sá | Zendy; Antônio Adolfo Simões | Zendy; Carlos Cardoso | Zendy; Eduardo Bezerra | Zendy

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Machine Learning Approaches to Extreme Weather Events Forecast in Urban Areas: Challenges and Initial Results

Author(s) -

Fábio Porto,

Mariza Ferro,

Eduardo Ogasawara,

Thiago Moeda,

Claudio Daniel Tenorio de Barros,

Anderson Chaves da Silva,

Rocío Zorrilla,

Rafael Silva Pereira,

Rafaela Castro,

João Victor Silva,

Rebecca Salles,

Augusto J. M. da Fonseca,

Juliana Hermsdorff,

Marcelo Magalhães,

Vítor J. Sá,

Antônio Adolfo Simões,

Carlos Cardoso,

Eduardo Bezerra

Publication year - 2022

Publication title -

supercomputing frontiers and innovations

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.375

H-Index - 16

eISSN - 2409-6008

pISSN - 2313-8734

DOI - 10.14529/jsfi220104

Subject(s) - extreme weather , precipitation , meteorology , weather prediction , population , task (project management) , computer science , numerical weather prediction , face (sociological concept) , predictive modelling , climatology , extreme learning machine , environmental science , machine learning , geography , climate change , engineering , artificial neural network , geology , systems engineering , social science , oceanography , demography , sociology

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