Visibility and Ceiling Nowcasting Using Artificial Intelligence Techniques for Aviation Applications

Cordeiro, Fabricio Magalhães; França, Gutemberg Borges; Neto, Francisco Leite de Albuquerque; Gültepe, Ismail

doi:10.3390/atmos12121657

Cited by 12 publications

(8 citation statements)

References 22 publications

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“…Realizou-se a busca na data de 06 de junho de 2022 com as palavras-chaves: "Aeroporto Afonso Pena" OR "Aeroporto Internacional Afonso Pena" OR "Afonso Pena Airport" OR "Afonso Pena International Airport", na seguinte na seguinte configuração: Tipo Contudo, os artigos encontrados pouco servem para a pesquisa pois nenhum apresenta informações sobre as vias urbanas, seus entornos, infraestrutura, nenhum dado neste aspecto. Oferecem informações acerca de: tecnicalidades da aviação (CORDEIRO et al, 2021;FIGUEIREDO et al, 2014), gestão de projetos em aeroportos (ANDRIANI et al, 2021;TADEU E SILVA, 2011), turismo (PAIVA et al, 2021 ou citação genérica (GUIZI E GANDARA, 2017).…”

Section: Capesunclassified

Avaliação De Traçados Geométricos Para Melhoria Dos Acessos Urbanos E Rodoviários Ao Aeroporto Afonso Pena

Ihlenfeld¹,

Amancio²,

Ramos³

et al. 2023

Transporte E Moradia No Brasil: Desafios E Particularidades

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Por muito tempo, o governo brasileiro não realizou investimentos condizentes com as necessidades na área de infraestrutura de transportes, em todas suas modalidades, especialmente nos aeroportos. Nesse contexto, a presente pesquisa buscou apresentar soluções técnicas de traçados geométricos para a melhoria dos acessos urbanos e rodoviários no Aeroporto Afonso Pena. Foi aplicada a revisão da literatura com base no Portal da CAPES e Oasisbr, revisão documental nos órgãos públicos competentes e pesquisa de campo nos anos de 2021 e 2022 no entroncamento urbano e rodoviário do Aeroporto. Quanto à revisão bibliográfica e documental, a literatura se demonstrou muito escassa em informações, assim como o plano diretor. Durante o período observado foram constatadas melhorias de infraestrutura urbana no local, contudo restritas à manutenção rotineira, sem mudanças significativas. A pesquisa levantou pontos de interesse para estudos preliminares e apresentou uma síntese que consiste na correção da congruência das ruas do acesso à trincheira da Rua Aviador Paulo Lepinski, na ampliação da mesma para mais uma pista e uma faixa de desaceleração vinda da BR-376 para entrar no Aeroporto. É necessária uma solução compatível com o porte do Aeroporto, dado os atuais investimentos, as sugestões de correção do projeto geométrico aqui propostas consistem em faixas de desaceleração e alargamento de vias, contudo necessitam de compatibilização com as interferências do local.

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Section: Capesunclassified

Avaliação De Traçados Geométricos Para Melhoria Dos Acessos Urbanos E Rodoviários Ao Aeroporto Afonso Pena

Ihlenfeld¹,

Amancio²,

Ramos³

et al. 2023

Transporte E Moradia No Brasil: Desafios E Particularidades

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“…Huber loss is widely used when the dataset has plenty of outliers as it reduces the impact of the outliers compared to the L 2 loss. The Huber Regression estimator has been proven to be reliable for achieving a large sample asymptotic property by Huber and Peter [25]. The loss function of Huber Regression is defined as follows:…”

Section: Artificial Intelligence Algorithmsmentioning

confidence: 99%

“…Recently, artificial intelligence methods have also made significant contributions in addressing model accuracy [20,21]. Against the backdrop of further applications of artificial intelligence methods in the field of aviation meteorology [22][23][24][25][26][27][28], this study aimed to explore the use of QAR data elements to predict EDRs for aircraft bumpiness based on artificial intelligence methods to attempt to break through the bottleneck of current aircraft bumpiness predictions based on highprecision aircraft flight status and different algorithm models.…”

Section: Introductionmentioning

confidence: 99%

Characteristic Analysis and Short-Impending Prediction of Aircraft Bumpiness over Airport Approach Areas and Flight Routes

Ding,

Zhang,

Wang

et al. 2023

Atmosphere

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Based on the Quick Access Recorder (QAR) data covering over 9000 routes in China, the monthly and intra-day distribution characteristics of aircraft bumpiness at different levels were analyzed, and the relationships between the eddy dissipation rate (EDR) and other aircraft flight status elements during bumpiness occurrence were also analyzed. Afterward, aircraft bumpiness routes were constructed using 19 machine learning models. The analyses show that (1) aircraft bumpiness was mainly concentrated between 0:00 a.m. and 17:00 p.m. Severe aircraft bumpiness occurred more frequently in the early morning in January, especially between 5:00 a.m. and 6:00 a.m., and moderate bumpiness always occurred from 3:00 a.m. to 11:00 a.m. (2) The relationship between the left and right attack angles and aircraft bumpiness on the routes was more symmetrical, with a center at 0 degrees, unlike in the approach area where the hotspots were mainly concentrated in the range of −5 to 0 degrees. In the approach area, the larger the Mach number, the more severe the bumpiness. (3) The performances of the Automatic Relevance Determination Regression (ARD), Partial Least Squares Regression (PLS), Elastic-Net Regression (ENR), Classification and Regression Tree (CART), Passive Aggressive Regression (PAR), Random Forest (RF), Stochastic Gradient Descent Regression (SGD), and Tweedie Regression (TWD) based models were relatively good, while the performances of the Huber Regression (HUB), Least Angle Regression (LAR), Polynomial Regression (PLN), and Ridge Regressor (RR) based models were very poor. The aircraft bumpiness prediction models performed best over the approach area of ZBDT (airport in Datong), ZULS (airport in Lhasa), ZPPP (airport in Kunming), and ZLQY (airport in Qingyang). The model performed best in predicting the ZLLL-ZBDT air route (flight routes for Lanzhou to Datong) with different prediction times.

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“…However, visibility and ceiling forecasts as a regression problem have been least explored and have recently gained some popularity. In a study conducted at Santos Dumont Airport Brazil, four machine learning models were used for both classification and regression forecasting of visibility, and regression forecasting for ceiling base height [13]. Similarly, a low visibility event forecasting study was carried out as both a classification and regression problem in Galicia, Spain using a large number of ML approaches [14].…”

Section: Introductionmentioning

confidence: 99%

Atmospheric Visibility and Cloud Ceiling Predictions With Hybrid IIS-LSTM Integrated Model: Case Studies for Fiji’s Aviation Industry

Raj,

Deo,

Sharma

et al. 2024

IEEE Access

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Atmospheric visibility and cloud ceiling forecasts are essential for the safety and efficiency of flight operations and the aviation industry. Routine hourly aviation meteorological observations are recorded at every airport. However, forecasts of these two meteorological parameters using artificial intelligence techniques are limited. This research utilizes data from two study sites in Fiji, Nadi, and Nausori International Airport, and proposes a hybrid Iterative Input Selection -Long Short-Term Memory (IIS-LSTM) integrated model to forecast the consecutive hour's visibility and ceiling parameters. The IIS algorithm acts as a feature selector from the global predictor matrix of predictor variables with its significant lagged inputs and the significant lagged inputs of the target variable, while the LSTM algorithm acts as the learning model and makes forecasts. The performance of the proposed hybrid IIS-LSTM model is evaluated using seven statistical score metrics and compared with four competing benchmark models. The evaluated results illustrate the superiority of the proposed hybrid IIS-LSTM integrated model and its advanced capability to generate accurate atmospheric visibility and cloud ceiling forecasts for the next consecutive hour compared to the benchmark models. The most important features selected were the second lagged input of visibility and first lagged input of rainfall to improve visibility forecasts while the first and the fifth lagged inputs of the total low cloud cover were paramount for accurate cloud ceiling forecasts. Considering the geography of the study sites, the overall efficacy of the IIS method is strongly advocated to screen most suitable model predictors and the subsequent integration of this input selection method with the LSTM predictive algorithm to attain enhanced performance of the hybrid IIS-LSTM forecast model. This objective model is therefore proposed to be an efficient and cost-effective predictive tool for atmospheric visibility and cloud ceiling forecasts, especially its applications in the aviation industry for aeronautical purposes.

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Visibility and Ceiling Nowcasting Using Artificial Intelligence Techniques for Aviation Applications

Cited by 12 publications

References 22 publications

Avaliação De Traçados Geométricos Para Melhoria Dos Acessos Urbanos E Rodoviários Ao Aeroporto Afonso Pena

Avaliação De Traçados Geométricos Para Melhoria Dos Acessos Urbanos E Rodoviários Ao Aeroporto Afonso Pena

Characteristic Analysis and Short-Impending Prediction of Aircraft Bumpiness over Airport Approach Areas and Flight Routes

Atmospheric Visibility and Cloud Ceiling Predictions With Hybrid IIS-LSTM Integrated Model: Case Studies for Fiji’s Aviation Industry

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