• IE interfaces
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• v.20 no.1
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• pp.41-48
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• 2007

The main purpose of this paper is cost reduction in absurd pilot positive expense and human accident prevention which is caused by in the pilot selection process. We use classification models such as logistic regression, decision tree, and neural network based on aptitude test results of 505 ROK Air Force applicants in 2001~2004. First, we determine the reliability and propriety against the aptitude test system which has been improved. Based on this conference flight simulator test item was compared to the new aptitude test item in order to make additional yes or no decision from different models in terms of classification accuracy, ROC and Response Threshold side. Decision tree was selected as the most efficient for each sequential flight training result and the last flight training results predict excellent. Therefore, we propose that the standard of pilot selection be adopted by the decision tree and it presents in the aptitude test item which is new a conference flight simulator test.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.4
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• pp.96-104
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• 2019

The response to climate change of international air transport industry might be initiated by ICAO's CORSIA (Carbon Offsetting and Reduction Scheme for International Aviation) which will impact on international airlines' flight operation behavior in the future. Though the airlines' efforts to reduce fuel consumption has been a major issue in economics of aviation industry, the improvement of fuel efficiency in flight operation will have additional impact on their profitability by introducing carbon emission cost. The fuel consumption in flight operation will be somewhat influenced by pilots' technical action for maneuvering aircraft during flight operation. This study will investigate pilots' behavior on decision for tactical aircraft control for mission flight. The data will be collected by the survey through sample pilots asking about their intention and perception on fuel savings during flight operations. The data will be analyzed by AHP process and the study will find out the elements and factors influencing pilots' behavior on technical decision of flight and their weights on fuel saving effects.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.3
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• pp.52-60
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• 2020

The purpose of this study was to analyze the effects of Student Majoring in Flight Operation's propensity, safety behavior and aeronautical decision-making. According to the analysis results, First, parents' criticism of perfectionism factor is found to have a negative effect on safety behavior. Second, student pilot's proactive personality has a positive impact on both safety participation behavior and safety compliance behavior. Third, both safety participation behavior and safety compliance behavior are found to have a significant effect on situation awareness, solution generation and solution implementation of decision making stages. Therefore, this study is intended to provide useful basic data that can be applied to studies such as appropriate psychological counseling, optimal training directions and teaching methods in order to cultivate excellent human resources through safe flight training.

• Journal of the Ergonomics Society of Korea
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• v.21 no.1
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• pp.1-14
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• 2002

The main purpose of this paper is to present selection criteria for ROK Airforce pilot training candidates in order to save costs involved in sequential pilot training. We use classification models such Decision Tree, Logistic Regression and Neural Network based on aptitude test results of 288 ROK Air Force applicants in 1994-1996. Different models are compared in terms of classification accuracy, ROC and Lift-value. Neural network is evaluated as the best model for each sequential flight test result while Logistic regression model outperforms the rest of them for discriminating the last flight test result. Therefore we suggest a pilot selection criterion based on this logistic regression. Overall. we find that the factors such as Attention Sharing, Speed Tracking, Machine Comprehension and Instrument Reading Ability having significant effects on the flight results. We expect that the use of our criteria can increase the effectiveness of flight resources.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.4
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• pp.154-163
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• 2020

The pilot's aeronautical decision-making during the flying greatly affects flight safety, and the importance of situational awareness has been greatly emphasized as a prerequisite for making the right decision. This is the reason why more research and interests are needed to help students entering the pilot training program develop excellent situational awareness from the initial stage of training. Situational awareness is closely related to long-term memory activities in human information processing, and pedagogy and cognitive psychology have emphasized the encoding techniques as an effective long-term memory method. This study was conducted to confirm whether pilot students' using the encoding techniques to learn flight education materials in the early stage of their training at domestic universities has a positive effect on improving their situational awareness.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.3
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• pp.50-59
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• 2014

It has been focused on that the major reasons of aircraft accidents resulted not from human error but from the failure of teamwork or communication in 1980's. Such opinions were suggested in the workshop, so called, "Resource Management on the Flight Deck" by NASA in 1979. The researchers agreed the fact the source of human error was originated from the failure in teamwork, communication or even in leadership of captain. Due to the rapid development of aircraft technologies, the reasons for aircraft accident could be easily found out. According to the analysis results of the technology, most of reasons for the accident might directly be connected not to human error or stick-Rudder skill but to situational awareness, communication, leadership or decision making in the aircraft. This paper has tried to research empirically the satisfaction of flight crews who have gone thorugh CRM training in the commercial airline. Based on the quantitative scale by J. Ford et al. (2014), this paper has proved which characteristics of CRM training has a positive impact on the overall satisfaction of CRM training. It was proven that the teamwork and decision making programs among CRM training have a major effect to the satisfaction level of flight crews.

• The Journal of Information Systems
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• v.31 no.3
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• pp.177-195
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• 2022

Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.2
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• pp.213-221
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• 2009

An aircraft collision accident is a disaster that causes great losses of inventories and lives. Though a collision avoidance warning function is provided automatically to pilots in the aircrafts by the enhancement of the aircraft capability, achieving fast decision-making to escape a collision situation is a complex and dangerous work for pilots. If an in-flight collision situation is controlled by the air traffic control system which monitors all airplanes in the air, it would be more efficient to prevent in-flight collisions because it can handle the emergency before the pilot's action. In this paper, we develop the collision avoidance warning function in the air traffic control system. Specifically, we design and implement the five stages of the collision avoidance function, and propose a visualization method which could effectively provide the operators with the trajectories and altitudes of the aircrafts in a collision situation. By developing an in-flight collision warning function in the air traffic control system that visualizes flight patterns through the state transition data of in-flight aircrafts on the flight path lines, it can effectively prevent in-flight collisions with traffic alerts. The developed function allows operators to effectively select and control the aircraft in a collision situation by providing the operators with the expected collision time, the relative distance, and the relative altitude while assessing the level of alert, and visualizing the alert information which includes the Attention-Warning-Alert phase via embodying the TCAS standard. With the developed function the air traffic control system could sense an in-flight collision situation before the pilot's decision-making moment.

• Journal of Aerospace System Engineering
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• v.1 no.3
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• pp.37-42
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• 2007

The flight safety system for the satellite launch vehicles is required in order to minimize the risk due to launch vehicle failure. For prompt and reliable decision of flight termination, the flight safety system usually uses multiple sensors to estimate launch vehicle's flight trajectory. In that case, multiple types of observed tracking data makes it difficult to identify the flight termination condition. Therefore, a fusion tracking filter handling the multiple tracking data is necessary for the flight safety system. This research developed a simulation software for generating multiple types of launch vehicle tracking data, and then processed the data with fusion filters.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.4
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• pp.73-79
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• 2010

Flight test is the final and a mandatory process for the development of unmanned aerial vehicles(UAVs) as well as manned. Since most UAVs fly in a low speed and are prone to adverse weather conditions such as air turbulence, atmospheric weather environment around flight test regions will be a critical item to be considered for a flight test planning for UAVs. In this paper, we suggest a decision method for a UAV flight test schedule based on weather conditions of surface and upper atmospheres and also introduce a program for an effective flight test planning through weather forecasts.