Application of the nonlinear autoregressive model with exogenous inputs for river level forecast in the Amazon
DOI:
https://doi.org/10.31686/ijier.vol10.iss3.3696Keywords:
Forecast, river level, NARX, Artificial IntelligenceAbstract
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..
References
ALBERTON, Gabriel Barreto et al. Aplicação de redes neurais artificiais para previsão de enchentes no rio Itajaí-Açu em Blumenau, SC, BrasiI. Revista Ibero-Americana de Ciências Ambientais, v. 12, n. 4, 2021. DOI: https://doi.org/10.6008/CBPC2179-6858.2021.004.0053
ALBUQUERQUE, Francisco Roberto. Os problemas causados pela cheia do rio Amazonas na área do bairro da Francesa na cidade de Parintins no ano de 2015. 2018.
ALENCAR, David B. et al. Hybrid approach combining SARIMA and neural networks for multi-step ahead wind speed forecasting in Brazil. IEEE Access, v. 6, p. 55986-55994, 2018. DOI: https://doi.org/10.1109/ACCESS.2018.2872720
ALVES, Luna Gripp Simões. Relatório para estabelecimento de cotas de referência para alerta hidrológico em Municipios da Amazônia Ocidental. 2021.
ARAÚJO, Carla Beatriz Costa de et al. Previsão Sazonal de Vazões para a Bacia do Orós (Ceará, Brasil) Utilizando Redes Neurais e a Técnica De Reamostragem dos K-vizinhos. Revista Brasileira de Meteorologia, v. 35, p. 197-207, 2020. DOI: https://doi.org/10.1590/0102-7786351015
BARBOSA DE ALENCAR, David et al. Different models for forecasting wind power generation: Case study. Energies, v. 10, n. 12, p. 1976, 2017. DOI: https://doi.org/10.3390/en10121976
BLÁZQUEZ-GARCÍA, Ane et al. Short-term office building elevator energy consumption forecast using SARIMA. Journal of Building Performance Simulation, v. 13, n. 1, p. 69-78, 2020. DOI: https://doi.org/10.1080/19401493.2019.1698657
CERRI, Ricardo. Introdução às Redes Neurais Artificiais com Implementações em R. In: Anais da I Escola Regional de Aprendizado de Máquina e Inteligência Artificial de São Paulo. SBC, 2020. p. 47-50.
CHANG, Wen-Yeau et al. A literature review of wind forecasting methods. Journal of Power and Energy Engineering, v. 2, n. 04, p. 161, 2014. DOI: https://doi.org/10.4236/jpee.2014.24023
CRISTALDO, Marcia Ferreira et al. [artigo retratado] redes neurais artificiais aplicadas à previsão de enchentes para região do pantanal no mato grosso do sul. Geosciences= Geociências, v. 39, n. 1, p. 191-201, 2020. DOI: https://doi.org/10.5016/geociencias.v39i1.13644
DE AMORIM, Renata Ferreira. A gestão dos recursos hídricos através da tríade soberania, sustentabilidade e desenvolvimento sustentável–recorte na Região Hidrográfica Amazônica. Anais dos Seminários de Iniciação Científica, n. 23, 2021. DOI: https://doi.org/10.13102/semic.v0i23.6679
DE MENDONÇA, Leonardo Melo et al. Modelagem chuva-vazão via redes neurais artificiais para simulação de vazões de uma bacia hidrográfica da Amazônia. Revista de Gestão de Água da América Latina, v. 18, n. 2021, 2021. DOI: https://doi.org/10.21168/rega.v18e2
FAVA, Maria Clara. Modelo de alerta hidrológico com base participativa usando sistema de informações voluntárias para previsão de enchentes. 2015. Tese de Doutorado. Universidade de São Paulo.
FINCK, Juliano Santos. Previsão em tempo atual de níveis fluviais com redes neurais artificiais: aplicação à bacia do Rio Taquari-Antas/RS. 2020.
GORODETSKAYA, Yulia; DA FONSECA, Leonardo Goliatt; DE MELO RIBEIRO, Celso Bandeira. PREVISÃO DE VAZÃO DE CURTO PRAZO UTILIZANDO REDES NEURAIS ARTIFICIAIS. ESTUDO DE CASO: RIO PARAÍBA DO SUL, 2017.
HAYKIN, S. O. Neural Networks and Learning Machines. 3 Prentice Hall. New York, 2008.
INMET. 2021. Acessado em: 18/08/2021. Disponível em: https://bdmep.inmet.gov.br/
MARACAJÁ, José Rosenilton de Araújo et al. Previsão regionalizada de vazão sazonal utilizando redes neurais artificiais. 2005.
MATKOVSKYY, romano; BOURAOUI, Taoufik. Aplicação de redes neurais a índices compostos de séries temporais curtas: Evidência do modelo não linear autoregressivo com entradas exógenas (narx). Journal of Quantitative Economics, v. 17, n. 2, pág. 433-446, 2019.
MCCULLOCH, Warren S.; PITTS, Walter. A logical calculus of the ideas immanent in nervous activity. The bulletin of mathematical biophysics, v. 5, n. 4, p. 115-133, 1943. DOI: https://doi.org/10.1007/BF02478259
MUÑOZ CHÁVEZ, Jairo José. Modelagem em espaço de estados e predição da geometria do cordão de solda no processo GMAW usando redes SVM, neurodifusa e recorrentes de alta ordem. 2020.
NATTRODT, Thaísy Nitis Mota; DIAS, Maria Das Graças Santos. As relações entre os recursos hídricos, a energia e a sustentabilidade na Amazônia. Brazilian Journal of Development, v. 7, n. 4, p. 38319-38339, 2021. DOI: https://doi.org/10.34117/bjdv7n4-341
PARENTE, Ricardo Silva et al. Application of the narx model for forecasting wind speed for wind energy generation”. International Journal of Development Research, v. 11, n. 04, p. 46461-46466, 2021.
PORTO DE MANAUS, O CORAÇÃO DO AMAZONAS. 2021. Acessado em: 18/08/2021. Disponível em: https://www.portodemanaus.com.br/?pagina=nivel-do-rio-negro-hoje
REIS, Leonardo Pequeno et al. Prognose da distribuição diamétrica na Amazônia utilizando redes neurais artificiais e autômatos celulares. Floresta, v. 48, n. 1, p. 93-102, 2018. DOI: https://doi.org/10.5380/rf.v48i1.52748
Serviço Geológico do Brasil (CPRM). Boletim de Monitoramento Hidrometereológico da Amazônia Ocidental. 2021.
SILVA, João Batista Lopes da. Modelos de previsão de enchentes em tempo real para o município de Nova Era MG. 2006.
SILVA, Marcos Cardoso et al. Aplicação de redes neurais artificiais na cultura do mogno (Khaya spp. e Swietenia spp.). Journal of Biotechnology and Biodiversity, v. 8, n. 1, p. 017-023, 2020. DOI: https://doi.org/10.20873/jbb.uft.cemaf.v8n1.csilva
SILVA, Maria do Socorro Rocha da et al. Bacia hidrográfica do Rio Amazonas: contribuição para o enquadramento e preservação. 2013.
SILVA, Maria do Socorro Rocha da; MIRANDA, Sebastião Átila Fonseca; SANTANA, Genilson Pereira. Bacia Hidrográfica do Rio Amazonas: Condições de suas águas versos Resolução n° 357/CONAMA/2005. Volume 6, Pags. 83-90, 2016.
VILELA, Leticia Biagi; MATEUS, Tiago Henrique de Abreu. APLICAÇÃO DE REDE NEURAL NARX PARA A PREVISÃO DO PREÇO DA SOJA. XXXVI Encontro nacional de engenharia de produção. 2016.
WANG, Wen-chuan et al. Improving forecasting accuracy of annual runoff time series using ARIMA based on EEMD decomposition. Water Resources Management, v. 29, n. 8, p. 2655-2675, 2015. DOI: https://doi.org/10.1007/s11269-015-0962-6
WUNSCH, Andreas; LIESCH, Tanja; BRODA, Stefan. Previsão dos níveis de água subterrânea usando redes autorregressivas não lineares com entrada exógena (NARX). Journal of hydrology, v. 567, p. 743-758, 2018. DOI: https://doi.org/10.1016/j.jhydrol.2018.01.045
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Gisele de Freitas Lopes, Manoel Henrique Reis Nascimento, Alexandra Amaro de Lima, Nadime Mustafa Moraes, José Roberto Lira Pinto Júnior, Ana Priscila Barbosa de Alencar, David Barbosa de Alencar
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyrights for articles published in IJIER journals are retained by the authors, with first publication rights granted to the journal. The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author for more visit Copyright & License.
How to Cite
Accepted 2022-03-06
Published 2022-03-01
Most read articles by the same author(s)
- Geovani da Silva Monteiro, Luiz André Martins Pereira, David Barbosa de Alencar, Antônio Estanislau Sanches, Carlos Eduardo de Oliveira, Igor Felipe Oliveira Bezerra, Reverse Aftermarket Logistics in E-Commerce a Case Study in a Manaus Microenterprise , International Journal for Innovation Education and Research: Vol. 7 No. 9 (2019): International Journal for Innovation Education and Research
- Oneida Ribeiro Tavares, Fabiana Rocha Pinto, David Barbosa de Alencar, Manoel Henrique Reis Nascimento, Piezoelectric Energy Characterization: Materials and Utilization , International Journal for Innovation Education and Research: Vol. 7 No. 11 (2019): International Journal for Innovation Education and Research
- Adilson Alves Góes, Fabiana Rocha Pinto, David Barbosa de Alencar, Gisele de Freitas Lopes, Proposal of LPS Implementation in Popular Buildings in Manaus City , International Journal for Innovation Education and Research: Vol. 7 No. 11 (2019): International Journal for Innovation Education and Research
- Rômulo de Araújo Reis, Bruna Moraes de Oliveira, Lívia da Silva Oliveira, David Barbosa de Alencar, Study of the Physical Aspects of Residential Soils of Iranduba - AM , International Journal for Innovation Education and Research: Vol. 7 No. 10 (2019): International Journal for Innovation Education and Research
- Fabrício dos Santos Silva, David Barbosa de Alencar, Alexandra Priscilla Tregue Costa, Marden Eufrasio dos Santos, Implementation of Time and Method Studies for Improvement Continues in Productive Efficiency of the Mini System Production Line , International Journal for Innovation Education and Research: Vol. 7 No. 11 (2019): International Journal for Innovation Education and Research
- João Bosco Rodrigues Pereira, David Barbosa de Alencar, Alexandra Priscilla Tregue Costa, Antônio Estanislau Sanches, Methodology for Indirect Material Control in a White Line Company , International Journal for Innovation Education and Research: Vol. 7 No. 11 (2019): International Journal for Innovation Education and Research
- Maurício de Jesus Carretilha, Fabiana Rocha Pinto, David Barbosa de Alencar, Gisele de Freitas Lopes, Quantification of CO2 Emissions by Top-down Method of Manaus Public and Private Transport Fleet , International Journal for Innovation Education and Research: Vol. 7 No. 11 (2019): International Journal for Innovation Education and Research
- João Vitor Barros Assunção, Renan Phelipe Rodrigues Pantoja, Bruno Pereira Gonçalves, David Barbosa de Alencar, Jean Mark Lobo de Oliveira, Comparative Analysis Between Native and Hybrid Mobile Applications , International Journal for Innovation Education and Research: Vol. 7 No. 11 (2019): International Journal for Innovation Education and Research
- Alyne Carvalho Farias, David Barbosa de Alencar, Alexandra Priscilla Tregue Costa, Antônio Estanislau Sanches, Application of queuing theory to a financial institution in the public service sector in the city of Manaus , International Journal for Innovation Education and Research: Vol. 7 No. 11 (2019): International Journal for Innovation Education and Research
- Marcilio Silva Almeida, Livia da Silva Oliveira, David Barbosa de Alencar, Francisco Carlos Tavares Amorim, Mechanical Analysis of Asphalt Pavements with Alternative Materials in Manaus - Amazonas , International Journal for Innovation Education and Research: Vol. 7 No. 10 (2019): International Journal for Innovation Education and Research