• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.2
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• pp.94-110
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• 1997

In the present study, a mean torque predictive model has been proposed and experimentally validated. It includes induction air mass model, fuel delivery model and mean production mode. Air induction and fuel delivery model considering dynamic behaviors of air induction and fuel delivery were proposed to predict the air-fuel ratio excursions under transient condition. Torque function model reflects thermal efficiency, volumetric efficiency, friction and effect of spark timing. In the spark timing model, knock limit and acceleration retard are included. Experiments were carried out to validate the simulation model for the step changes of throttle at constant engine speed. The results show reasonable agreements between simulation and experiment at fully warmed condition. Using this model, fueling strategies are varied with fast throttle open and it can predict air-fuel ratio excursion and IMEP.

• The Korean Journal of Applied Statistics
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• v.5 no.1
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• pp.59-80
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• 1992

This paper is concerned with the development and application of a stochastic model for winter air-temperature of Seoul area. The annual and interannual flucturations of the regression trend, periodicity and dependence of the air-temperature are analyzed based on the data during the past 30 years(1959-1989). A statistical procedure for using the stochastic model to predict the air-temperature is proposed. Some statistical characteristics of winter air-temperature including unusual air-temperature and Samhansaon are also discussed.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.12
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• pp.1316-1322
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• 2006

The purpose of this study is to analyze the pattern distribution of the odorous compounds and air pollutants from the inventory sources in the Cheon-an second industrial complex. Twelve analysis including specified odor materials and air pollutants were concurrently measured during the month of August, 2005 to evalaute odor emission characterization in m3;or treatment facilities. Also, Concentration of air pollutants has been calculated by ISCST3 in ISC3 models. A Korean air diffusion modeling software, Air Master, was developed on a basis of diffusion theories adopted in U.S. EPA's ISC3 model to assess the air quality impact from the stacks. This investigation will be executed how large the complex pollutant sources such as industrial complex contribute to atmospheric environment and air quality of the surrounding the area as predicting by comparing and analyzing results of odorous compounds and air pollutants diffusion concentration model.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2010.04a
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• pp.570-571
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• 2010

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.11
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• pp.994-1003
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• 2000

Control algorithms for the absorption air conditioning system may be developed by suing dynamic models of the system. The simplified effective dynamic models, which can predict the dynamic behaviors of the system, may help the development of effective control algorithms for the system. In this study, a dynamic simulation program for the absorption air conditioning system was developed. Dynamic models for an absorption chiller, a cooling tower, an air handling unit, a boiler, a three way valve, a controller, and a duct were developed and programed. Control algorithms for the absorption chiller, the cooling tower, and the air handling unit were selected, and analyzed to show the effectiveness of dynamic models. From the simulation results, it may be concluded that this simulation program may be effectively used for the development of optimal control algorithms of the absorption air conditioning system.

• Journal of Korean Society of societal Security
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• v.2 no.1
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• pp.65-74
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• 2009

In this study, the air pollution management system based GIS has been developed to estimate the emission rate and air pollution modeling of air pollutants, effectively. This system is able to estimate emission rate of air pollutant and to analyze the emission characteristics with high spatial and temporal resolution. air pollution modeling. The air pollution management system was applied to Gwangyang Bay including large industry complex with a large number of emission sources. The air pollution management system was constructed using the spatial database of emission sources in Gwangyang Bay. It was found that the estimated emission rates of air pollutants is similar to the emission characteristics in Gwangyang Bay. Also, the spatial distribution of pollutants was similar to the location of emission sources. The predicted results of air pollution model was showed a good correlation coefficient (0.75) for TSP. The air pollution management system is expected to be effective tool (database system (GIS)) for the management and the control of air pollution.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.260-269
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• 2022

In this paper, We propose an anomaly detection model using deep neural network to automate the identification of outliers of the national air pollution measurement network data that is previously performed by experts. We generated training data by analyzing missing values and outliers of weather data provided by the Institute of Environmental Research and based on the BeatGAN model of the unsupervised learning method, we propose a new model by changing the kernel structure, adding the convolutional filter layer and the transposed convolutional filter layer to improve anomaly detection performance. In addition, by utilizing the generative features of the proposed model to implement and apply a retraining algorithm that generates new data and uses it for training, it was confirmed that the proposed model had the highest performance compared to the original BeatGAN models and other unsupervised learning model like Iforest and One Class SVM. Through this study, it was possible to suggest a method to improve the anomaly detection performance of proposed model while avoiding overfitting without additional cost in situations where training data are insufficient due to various factors such as sensor abnormalities and inspections in actual industrial sites.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2003.05b
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• pp.349-350
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• 2003

ISCST 등의 대기확산모델은 모두 EPA에서 개발된 것으로 모델 운영에 사용되는 모든 데이터가 미국의 실정에 맞게 프로그램 되어 있다. 특히 ISC모델을 운영하기 위하여 필요로 하는 기상자료를 생성하는 MIXHTS와 PCRAMMET등은 미국 기상청이나 기타 기상관련 기관에서 발표하는 자료를 사용하도록 되어있다. 따라서 ISC를 운영하는데 있어 국내 기상자료를 해당하는 형태로 전환해야 하는 번거로움이 있으며 우리나라 기상청에서 발표하는 기상자료의 형태와 MIXHTS PCRAMMET에서 요구하는 기상자료형태를 모두 알고 있어야만 ISC를 운영하기 위한 올바른 기상자료를 만들 수 있었다. (중략)

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.472-479
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• 2024

Half of the world's total population lives in cities, continuous urbanization is progressing, and the urban population is expected to exceed two-thirds of the total population by 2050. To resolve this phenomenon, the Korean government is focusing on building a new urban air mobility (UAM) industrial ecosystem. Airlines are also part of the UAM industry ecosystem and are preparing to improve efficiency in safe operations, passenger safety, aircraft operation efficiency, and punctuality. This study performs demand forecasting using time series data on the number of daily passengers on Korean Air's Gimpo to Jeju route from 2019 to 2023. For this purpose, statistical and machine learning models such as SARIMA, Prophet, CatBoost, and Random Forest are applied. Methods for effectively capturing passenger demand patterns were evaluated through various models, and the machine learning-based Random Forest model showed the best prediction results. The research results will present an optimal model for accurate demand forecasting in the aviation industry and provide basic information needed for operational planning and resource allocation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.195-201
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• 2017

Urbanization and industrialization have led to a severe deterioration in urban air qualities. As an air pollution is closely associated with human health, citizen has a growing concern about the air quality policy to improve their residential environment. Due to the recently advance in web- and mobile computing technologies, citizens can easily access various air quality information and public authorities utilize the social media service to communicate citizens with air quality issues. Also citizens' participation and role has been increased to improve urban air qualities. Thus, to meet the technical and societal changes, a GIS-based air quality information system is developed based upon the Ubiquitous Public Access (UPA) model in ISO19154. The proposed system employs the context information model to provide air quality information depending on citizens' health conditions and locations. Also, citizens can present their perceptions of an air quality at their current location Public authorities can thus utilize the citizens' perceptions when establishing new air quality policies.