A case study on the effect of meteorological events on the efficiency of flight training organization

Tatli, Ali; Bocu, Erdogan; Filik, Tansu; Karakoç, T. Hikmet

doi:10.1108/aeat-10-2021-0295

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…The project will provide personalized and accurate weather information. The research results of this project are important for improving the level and quality of meteorological information services in China and promoting the development process of meteorology 3,4 .…”

Section: Introductionmentioning

confidence: 99%

Intelligent meteorological information acquisition service platform based on Internet of Things

Chang

2023

International Conference on Computer Application and Information Security (ICCAIS 2022)

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Although China’s meteorological departments have established a considerable number of national meteorological information monitoring networks, the information gap between meteorological departments, agricultural experts and ordinary farmers makes it impossible for them to accurately determine the objectives of agricultural production and improve the quality and efficiency of standard weather forecasts. This document addresses these issues. Therefore, this paper discusses the meteorological data collection method, collection equipment, crop fertility knowledge base and service forecast model based on the internet of things (IoT), real-time sensor data and the national integrated meteorological information sharing platform (CIMISS), develops meteorological data collection equipment suitable for small-scale agricultural environment, and develops an intelligent IoT service platform for integrated meteorology. The system has been demonstrated in a city meteorological bureau, and the results show that it can provide technical support for efficient planting, accurate management and customized services of agricultural production.

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Section: Introductionmentioning

confidence: 99%

Intelligent meteorological information acquisition service platform based on Internet of Things

Chang

2023

International Conference on Computer Application and Information Security (ICCAIS 2022)

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“…The implementation of metacognitive strategies was found to optimize pilots' cognitive resource coordination. Tatli, Ali and colleagues [8] explored the ramifications of meteorological conditions on flight training. Their data-driven investigation highlighted that adverse weather events augmented the workload of flight trainers, extended training durations, and intensified maintenance and repair activities, culminating in a significant surge in flight training expenses.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Training Cost and Difficulty for Aircraft-Type Transition Based on Similarity Assessment

Cao,

Zhang,

Feng

2024

Aerospace

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As aviation technology advances, numerous new aircraft enter the market. These not only offer airlines technological and fuel efficiency advantages but also present the challenge of how to conduct pilots’ aircraft-type transition training efficiently and economically. To address this issue, this study designed a methodology to quantitatively assess the similarity in panel display control design and standard operating procedures (SOPs) between aircraft types. Then, by combining the results of a questionnaire survey on A320, A330, B737, and B777 transition training and training cost data, it was verified quantitatively that inter-aircraft similarity has a positive impact on reducing the difficulty and cost of transition training. Taking the similarity in aircraft types as a feature, the KNN algorithm was used to successfully construct a difficulty prediction model for the training program of aircraft-type transition training. To overcome the limitation of insufficient training cost data volume, this study adopts the transfer learning method to construct a prediction model of the transition training cost, and the final significant prediction accuracy proves the effectiveness of the method. The research in this paper not only provides strong data support for the resource planning and cost management of airlines’ aircraft-type transition training but also provides new research perspectives and methodological guidance for the field of aviation training.

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Short‐term multivariate airworthiness forecasting based on decomposition and deep prediction models

Tatli,

Filik,

Bocu

et al. 2024

Journal of Forecasting

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This study introduces a model for predicting airworthiness in terms of meteorology information within the viewpoint of not only formal regulations but also informal rules based on acquired indicators from flight training organization experience (AIs‐FTOE). The case study is carried out in the Hasan Polatkan Airport which is used by the Department of Flight Training of Eskişehir Technical University (ESTU‐P), which is also recognized as a flight training organization. Within the study, the constraints (derived from regulations and AIs‐FTOE) and the data set used in models are explained. Also, the models are introduced based on the gated recurrent unit (GRU) and long short‐term memory (LSTM) with the use of empirical mode decomposition (EMD) and variational mode decomposition (VMD). Finally, a model‐selective mechanism (MSM) is proposed to use the models in common. The findings show that the models presented in the study produce successful results that can be used in flight training organization's (FTO) planning studies. The MSM uses GRU and LSTM together with decomposition techniques to provide more advanced prediction capabilities. When the literature is examined, it is observed that although meteorological conditions are of vital importance in the efficiency of FTOs, there are not enough studies on airworthiness based on meteorology. So, a model that will assist in scheduling plans is presented for FTOs. Airworthiness analysis of forecasting can provide a comprehensive reference to support planning efficiency in FTOs. To the authors' knowledge, this study will be the first in the literature on airworthiness that presents the MSM using a hybrid deep learning algorithm and decomposition of time series models in concurrent.

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A case study on the effect of meteorological events on the efficiency of flight training organization

Cited by 4 publications

References 18 publications

Intelligent meteorological information acquisition service platform based on Internet of Things

Intelligent meteorological information acquisition service platform based on Internet of Things

Prediction of Training Cost and Difficulty for Aircraft-Type Transition Based on Similarity Assessment

Short‐term multivariate airworthiness forecasting based on decomposition and deep prediction models

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