• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1700-1705
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• 2009

In general, short term load forecasting is based on the periodical load pattern during a day or a week. Therefore, the conventional methods do not expose stable performance to every day during a year. Especially for anomalous weather conditions such as typhoons, the methods have a tendency to show the conspicuous accuracy deterioration. Furthermore, the tendency raises the reliability and stability problems of the conventional load forecast. In this study, a new load forecasting method is proposed in order to increase the accuracy of the forecast result in case of anomalous weather conditions such as typhoons. For irregular weather conditions, the sensitivity between temperature and daily load is used to improve the accuracy of the load forecast. The proposed method was tested with the actual load profiles during 14 years, which shows that the suggested scheme considerably improves the accuracy of the load forecast results.

• Journal of the Korea Convergence Society
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• v.5 no.1
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• pp.9-15
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• 2014

Traffic accidents are caused by a variety of factors. Among the factors that cause traffic accidents are weather conditions at the time. There is a difference in the percentage of deaths according to traffic accidents, due to the weather conditions. In order to reduce the number of deaths due to traffic accidents, to predict the incidence of traffic accidents that occur in response to weather conditions is required. In this paper, it propose a model to predict the incidence of traffic accidents caused by weather conditions. Predictive modeling was applied to the theory of Markov processes. By applying the actual data for the proposed model, to predict the incidence of traffic accidents, it was compared with the number of occurrences in practice. In this paper, it is to support the development of traffic accident policy with the change of weather.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.1 no.1
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• pp.3-11
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• 1972

The outdoor design conditions for the locality are the basic problem in the design of air conditioning system. The ideal solution to the basic problem is to design a building that has a capacity at maximum output just equal to the load which develops the most severe conditions for the locality occur, but in most cases, economics interferes the attainment of the ideal. Studies of weather records show that the most severe conditions do not repeat themselves every year. The weather conditions of principal cities such as Seoul, Inchon, Suwon, Taegu, Chonju, Ulsan, Kwangju, Pusan and Mokpo in Korea have been analyzed to determine the probability of occurrence of certain temperatures according to recent 10 years $(1960\∼1969)$ weather records. The outdoor conditions for winter air conditioning design are shown on Table 2. The outdoor conditions for summer air condioning design are shown on Table 7. Heating degree days are shown on Table 10 and 11.

• IE interfaces
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• v.13 no.4
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• pp.646-657
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• 2000

We developed an efficient small sized weather condition forecasting system (WFS). A cheap NT-server was utilized for handling a large amount of data, while traditional WFS has conventionally relied on Unix based workstation server. The proposed WFS contains automatic weather observing system (AWS). AWS was designed for collecting weather conditions automatically, and it was linked to WFS in order to provide various weather condition information. The existing two phase scheme and chain code algorithm were used for transforming AWS's data into WFS's data. The WFS's data were mapped into geometric information system using various display techniques. Finally the transformed WFS's data was also converted into JPG (Joint Photographic Group) data type, and the final JPG data could be accessible by others though Internet. The developed system was implemented using WWW environment and has provided weather condition forecasting information. Real case is given to show the presented integrated WFS with detail information.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.1
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• pp.25-32
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• 2016

This study deals with the light environments and weather conditions affecting to the night illuminance over the Korean peninsula. The experiment was executed to analyze the effects on the illuminance at separate sites(Gyeryong and Pilseung) considering the different light environments. The analysis was applied to illuminance measurement from the lightmeter, which was developed for the IYA(International Year of Astronomy) 2009, in order to observe the illuminance of areal networks. The weather observations, such as the cloud cover and visibility, were used to understand the quantitative influence of the illuminance to the selected sites. The results show that the illuminance measurements are significantly different from data of the operational illuminance prediction model which simply applies extinction effect for the illuminance. It shows that these differences are caused by the light environments and weather conditions for each site. Therefore, it can be confirmed that the night illuminance is the output of interaction with the characteristics of light for luminous sources.

• Proceedings of the KIEE Conference
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• 2007.04b
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• pp.99-102
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• 2007

Infrared thermography is one of the most valuable and cost-effective diagnostic techniques for predictive maintenance on electrical systems. For the installations, the thermography can identify major problems, which if left unattended could lead to breakdowns. The result thermal images depend upon operator skills, inspection technique, and weather conditions. When the thermographer is applied to remote monitoring, the conditions of the systems are not perfectly analyzed because operators are hard to know the weather effects of the installed place. Therefore, this paper defines the effect by weather conditions these factors will influence the final results. The purpose of this paper is to define the weather effects that a thermographer needs to consider for successful condition analysis.

• Smart Media Journal
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• v.8 no.1
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• pp.82-91
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• 2019

This study provides the analysis and prediction of fruits diseases related to weather conditions (temperature, wind speed, solar power, rainfall and humidity) using Linear Model and Poisson Regression. The main goal of the research is to control the method of fruits diseases and also to prevent diseases using less agricultural pesticides. So, it is needed to predict the fruits diseases with weather data. Initially, fruit data is used to detect the fruit diseases. If diseases are found, we move to the next process and verify the condition of the fruits including their size. We identify the growth of fruit and evidence of diseases with Linear Model. Then, Poisson Regression used in this study to fit the model of fruits diseases with weather conditions as an input provides the predicted diseases as an output. Finally, the residuals plot, Q-Q plot and other plots help to validate the fitness of Linear Model and provide correlation between the actual and the predicted diseases as a result of the conducted experiment in this study.

• Asian Journal of Business Environment
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• v.14 no.3
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• pp.1-11
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• 2024

Purpose: This study analyzes the impact of weather conditions, holidays, and sporting events on beer sales, providing insights for market strategy and inventory management in the beer industry. Research design, data and methodology: Beer types were classified into Lagers and Ales, with further subcategories. The study utilized weekly retail sales data from January 2018 to August 2020, provided by Nielsen Korea. An ARMAX model was employed for time-series analysis. Results: The analysis revealed that increasing temperatures positively influence sales of Pilsners and Pale Lagers. Conversely, higher precipitation levels negatively affect overall Lager sales. Among Ales, only Stout sales showed a significant decrease with increased rainfall. Sunshine duration did not significantly impact sales for any beer type. Humidity generally had little effect on beer sales, with the exception of Amber Lagers, which showed sensitivity to humidity changes. Holidays and sporting events were found to significantly boost sales across most beer types, although the specific impacts varied by beer category. Conclusions: This study offers a detailed analysis of how weather conditions and specific events influence different beer type sales. The findings provide valuable insights for breweries, beer processors, and retailers to optimize their market strategies and inventory management based on weather forecasts and seasonal events. By understanding the consumption patterns of each beer type in relation to environmental factors, businesses can better anticipate demand fluctuations and tailor their operations accordingly.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.1
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• pp.45-58
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• 2020

According to the Ministry of Land, Infrastructure and Transport press release ('18.12.21.) The amendment of the Aviation Business Act will reduce the capital requirements for aviation leisure operators and make it easier to enter aviation leisure businesses by improving regulations on small air transportation business. In addition, as the scale of the UAV(Unmanned Aerial Vehicle) sector is expected to increase globally, the dramatic increase in low altitude operating aircraft, including this, must be taken into account. The low altitude aircraft category is divided into small airplanes, helicopters, light aircrafts and ultra-light aircrafts, and instructors include school instructor pilots and student pilots, military and national helicopter pilots, and aviation leisure operators. In case of low altitude aircraft, there are cases of canceling operations due to low visibility and low clouds, and aircraft accidents due to excessive operation and sudden weather phenomenon. Therefore, in order to prevent low-altitude aircraft accidents, a safe flight plan based on weather conditions and weather forecasts and more accurate and local weather forecasts and weather forecast data are needed to prepare for the rapidly changing weather conditions.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.285-291
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• 2012

Generally, the rainfall and the influent of wastewater treatment plants (WWTPs) have strong relationship at the case of combined sewers. With the fact that the influent variations in terms of quantity and sewage quality is the most common and significant disturbance, the impact factor to the characteristics of sewage should be searched for. In this paper, the relationship between weather conditions such as humidity, temperature and rainfall and influent flowrate and contaminant concentration was analysed using factor analysis. Additionally, 3 influent types were deduced using cluster analysis and the distributions of operational variables were compared to the each groups by one-way ANOVA. The applied dataset were clustered to three groups that have the similar weather and influent conditions. These different conditions can cause the different operating conditions at WWTPs. That is, the Group 1 is for the condition with high humidity and rainfall, so DO concentration in the reactor was very high but MLSS concentration was very low because of too large flowrate. However, the Group 3 is classified to the case having low humidity, temperature, and rainfall, therefore, the SRT was the longest and the SVI was the highest due to the worst settleability in the winter for a year.