• 한국정보시스템학회지:정보시스템연구
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• 제31권3호
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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.

• 한국항공운항학회지
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• 제18권4호
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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.

• Journal of information and communication convergence engineering
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• 제21권3호
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• pp.225-232
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• 2023

Owing to advancements in intelligent transportation systems (ITS) and artificial-intelligence technologies, various machine-learning models can be employed to simulate and predict the number of traffic accidents under different weather conditions. Furthermore, we can analyze the relationship between weather and traffic accidents, allowing us to assess whether the current weather conditions are suitable for travel, which can significantly reduce the risk of traffic accidents. In this study, we analyzed 30000 traffic flow data points collected by traffic cameras at nearby intersections in Washington, D.C., USA from October 2012 to May 2017, using Pearson's heat map. We then predicted, analyzed, and compared the performance of the correlation between continuous features by applying several machine-learning algorithms commonly used in ITS, including random forest, decision tree, gradient-boosting regression, and support vector regression. The experimental results indicated that the gradient-boosting regression machine-learning model had the best performance.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제11B권4호
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• pp.169-174
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• 2001

A novel simulation scheme of transient phenomenon for the photovoltaic (PV) generation system under the real weather conditions has been proposed in this paper. A grid connected PV array is simulated using PSCAD/EMTDC. The transient changes of the output current of PV array under the real weather conditions is described and the output current of DC/AC converter flowing through the utility power network is also analyzed with the PWM switching width. Moreover, the MPPT control of PV generation system is combined to the system during the simulation for the comparison purposes of the control schemes. The outcome of the simulation demonstrates the effectiveness of the proposed simulation scheme. The result shows that the cost effective verifying for the efficiency or availability and stability of PV generation systems and the comparison research of various control schemes like MPPT under the same real whether conditions are eventually possible.

• Journal of Advanced Research in Ocean Engineering
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• 제4권2호
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• pp.53-65
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• 2018

The load condition significantly influences ship maneuverability in calm water. In this research, the effect of the load condition on turning performance of a very large crude oil carrier (VLCC) sailing in adverse weather conditions is investigated by an MMG-based maneuvering simulation method. The relative drift direction of the ship in turning to the wave direction is $20^{\circ}-30^{\circ}$ in ballast load condition (NB) and full load condition (DF) with a rudder angle $35^{\circ}$ and almost constant for any wind (wave) directions. The drifting displacement in turning under NB becomes larger than that under DF at the same environmental condition. Advance $A_d$ and tactical diameter $D_t$ become significantly small with an increasing Beaufort scale in head wind and waves when approaching, although $A_d$ and $D_t$ are almost constant in following wind and waves. In beam wind and waves, the tendency depends on the plus and minus of the rudder angle.

• 한국국방경영분석학회지
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• 제23권1호
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• pp.76-87
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• 1997

This paper deals with reliability and MTTF analysis of a non-repairable man-machine system operating under different weather conditions. The system consists of a hardware(machine) and a two-operator standby subsystem such as the air combat maneuvering of fighters with dual seat. The failure times for the subsystems follow the exponential distribution with constant parameter. By considering not only the effect on hardware component but also the weather conditions and human performance factors such as the operator's errors, a Markov model is presented as a method for evaluating the system reliability of time continuous operation tasks. Laplace transforms of the various state probabilities have been derived and then reliability of the system, at any time t, has been computed by inversion process. MTTF has also been computed.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.368-368
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• 2022

The Soil and Water Assessment Tool (SWAT) has been widely used to simulate the long-term hydrological conditions of a catchment. Two output variables, outflow and sediment yield have been widely investigated in the field of water resources management, especially in determining the conditions of ungauged subbasins. The presence of missing data in weather input data can cause poor representation of the climate conditions in a catchment especially for large or mountainous catchments. Therefore, in this study, a custom module was developed and evaluated to determine the efficiency of utilizing basic spatial interpolation methods in the estimation of weather input data. The module has been written in Python language and can be considered as a pre-processing module prior to using the SWAT model. The results of this study suggests that the utilization of the proposed pre-processing module can improve the simulation results for both outflow and sediment yield in a catchment, even in the presence of missing data.

• 대한토목학회논문집
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• 제32권1D호
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• pp.23-31
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• 2012

부산광역시는 2007년부터 시내버스 준공영제를 시행하고 있으며 급격히 증가하고 있는 재정지원금이 큰 문제로 대두되었다. 현재 부산시의 재정 상태를 감안한 경우 시내버스 준공영제의 성공 여부는 매년 투입되어야 하는 재정지원금을 연차적으로 감소시켜 나가야 하는 부분이다. 부산시 재정부담을 완화하기 위해서는 시내버스 이용을 보다 편리하게 하여 버스 이용객의 수요를 지속적으로 증가시켜야 할 것이다. 교통수요에 영향을 미치는 기상조건을 살펴보면 눈, 안개, 비 등이 있으며 이러한 기상조건은 통행자들의 수단선택에 영향을 미쳐 결과적으로 버스 이용의 감소를 가져온다. 그리하여 기상 악화시 이용률 저하는 수익금 감소로 이어지게 되어 부산시의 막대한 공공재정 부담으로 돌아오게 된다. 본 연구에서는 기상 상태에 따른 교통수단간 수송 분담률을 파악하여 기상 악화시 버스 승객이 타 교통수단으로 전환하는 패턴을 분석하고 설문조사를 통해 타 수단으로 전환하는 이유를 분석함으로써 향후 대중교통시설 및 환승체계 구축 등 버스정책 수립에 필요한 정책적 시사점을 도출하는데 목적이 있다.

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2006년도 추계학술발표회
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• pp.303-308
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• 2006

이 연구의 목적은 부산항에 입항하는 대형 콘테이너 선박의 안전 접안 조종을 위한 한계풍속을 설정하는데 있다. 계산결과, 정상풍속 13.5m/sec 이하의 바람에서는 예선 4500H.P.의 Z. peller 2척을 이용하여 안전 접안 조선하는데 큰 위험이 없음을 알았다. 그러나 돌풍율 25%를 포함한 강풍 16.9m/sec 이상의 기상상태에서는 선박조종이 위험하게 됨을 알았고, 돌풍율을 포함하여 풍속이 16.9m/sec 에 달하는 강풍하에서 대형 콘테이너 선박을 부득이 접안 조종할 때는 4500 H.P.Z. peller 3척으로 조선보조를 받아야 함을 알았다.

• 대한전기학회논문지:전력기술부문A
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• 제52권6호
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• pp.307-315
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• 2003

This paper proposes a novel simulation method of WPGS (Wind Power Generation System). The rotation speed control method of turbine under variable wind speed using the pitch control is proposed. Moreover, when wind speed exceeds the cut-out wind speed, the turbine will be stopped by controlling pitch angle to 90$^{\circ}$, otherwise it will be controlled to steady-state operation. For the purpose of effective simulation, the SWRW (Simulation method for WPGS using Real Weather condition) is used for the utility interactive WPGS simulation in this paper, in which those of three topics for the WPGS simulation: user-friendly method, applicability to grid-connection and the utilization of the real weather conditions, are satisfied. It is impossible to consider the real weather conditions in the WPGS simulation using the EMTP type of simulators and PSPICE, etc. External parameter of the real weather conditions is necessary to ensure the simulation accuracy. The simulation of the WPGS using the real weather conditions including components modeling of wind turbine system is achieved by introducing the interface method of a non-linear external parameter and FORTRAN using PSCAD/EMTDC in this paper. The simulation of long-term, short-term, over cut-out and under cut-out wind speeds will be peformed by the proposed simulation method effectively. The efficiency of wind power generator, power converter and flow of energy are analyzed by wind speed of the long-term simulation. The generator output and current supplied into utility can be obtained by the short-term simulation. Finally, transient-state of the WPGS can be analyzed by the simulation results of over cut-out and under cut-out wind speeds, respectively.