APPLICATION OF THE NONLINEAR AUTOREGRESSIVE MODEL WITH EXOGENOUS INPUTS FOR RIVER LEVEL FORECAST IN THE AMAZON
Item
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Tipo do ITEM
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Artigo Ciêntifico
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Título do Artigo
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APPLICATION OF THE NONLINEAR AUTOREGRESSIVE MODEL WITH EXOGENOUS INPUTS FOR RIVER LEVEL FORECAST IN THE AMAZON
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Descrição
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The present work is justified by three basic lines that involve the problem of the theme, which are the use
of Artificial Intelligence, the problem of floods in the Amazon and the issue of technology in favor of
decision making. The environmental impacts caused by economic and social factors are problems
portrayed in scenarios such as floods and ebbs of rivers, bringing up situations such as an increase in
diseases, reduction of agricultural production in locations that depend on accurate geological control, in
addition to the increase in erosive processes. in risk locations. Thus, the use of AI to predict the river level,
which consequently can minimize problems arising from floods that cause an environmental impact, is
highly possible, since when it is known in advance that an event is close to happening, decisions can be
taken so that the impacts be smaller. This work models and applies NARX to forecast the river level in the
Amazon with variables of easy access and implementation through the MATLAB software, in order to
contribute with a forecast model capable of predicting a possible flood from the river level.
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Abstract
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The present work is justified by three basic lines that involve the problem of the theme, which are the use
of Artificial Intelligence, the problem of floods in the Amazon and the issue of technology in favor of
decision making. The environmental impacts caused by economic and social factors are problems
portrayed in scenarios such as floods and ebbs of rivers, bringing up situations such as an increase in
diseases, reduction of agricultural production in locations that depend on accurate geological control, in
addition to the increase in erosive processes. in risk locations. Thus, the use of AI to predict the river level,
which consequently can minimize problems arising from floods that cause an environmental impact, is
highly possible, since when it is known in advance that an event is close to happening, decisions can be
taken so that the impacts be smaller. This work models and applies NARX to forecast the river level in the
Amazon with variables of easy access and implementation through the MATLAB software, in order to
contribute with a forecast model capable of predicting a possible flood from the river level.
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Língua do arquivo
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inglês
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Data da Publicação
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Ano 2021
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Palavra-chave
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Forecast
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River level
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NARX
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Artificial Intelligence
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Autores
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Gisele de Freitas Lopes
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Manoel Henrique Reis Nascimento
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Local
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ITEGAM - MANAUS, 2022
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Áreas de Conhecimento
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Energia e Meio Ambiente
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Turma
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Turma 01
