Open AccessAPPLICATION OF THE NONLINEAR AUTOREGRESSIVE MODEL WITH EXOGENOUS INPUTS FOR RIVER LEVEL FORECAST IN THE AMAZON
Author(s) -
Gisele de Freitas Lopes,
Manoel Henrique Reis Nascimento,
Alexandra Amaro de Lima,
Nadime Mustafa Moraes,
José Roberto Lira Pinto,
Ana Priscila Barbosa de Alencar,
David Barbosa de Alencar
Publication year - 2022
Language(s) - English
Resource type - Journals
ISSN - 2411-2933
DOI - 10.31686/ijier.vol10.iss3.3696
Subject(s) - amazon rainforest , flood myth , computer science , work (physics) , river flood , nonlinear autoregressive exogenous model , operations research , water resource management , environmental science , artificial neural network , geography , artificial intelligence , mathematics , engineering , mechanical engineering , ecology , archaeology , biology
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..