• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.11a
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• pp.213-217
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• 2009

Weather factors affect cost increases and progress management under construction. Because progress schedule is delayed by weather factors, the construction costs are increased. It is an essential element to control the progress schedule applying weather factors to the progress management. This study applies monthly working-day percentages which is estimated by databases of past weather information to RTPM system. Through do progress management in construction projects exactly, will try to minimize risk of process control that do that is to weather factors. Also, will compare calamity in safety supervision side that do that is to weather factors beforehand. Based on the factors and the expected impact of factors together with the weather data during the last 50 years in Seoul region gathered from Korea. Through it, calculated number of month working day of RCA's structural steel work. Studied way that apply to RTPM system.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.155-160
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• 2024

Weather indexes such as temperature, humidity, wind speed and air pressure have been studied for diverse life-related factors: Food poisoning, discomfort, and others. In that, the Korea Meteorological Administration(KMA) has been released indexes such as 'Life industrial weather information', 'Safety weather information', and even 'picnic weather information' that shows how an weather like to enjoy picnic. Those weather-life effects also reveal on shopping preference such as an weather affects offline shopping purchase behaviors especially big-marts because they have outside leisure activity attribute However, since online shopping has not physical attribute, weather factors may not affect on same way to offline. Although previous researches have focused on psychological factors that have been utilized in marketing criteria, this research utilize KMA weather dataset that affects psychological factors. This research utilize 1,033 online survey for SEM analysis to clarify relationships between weather factors and online shopping purchase behaviors. As a result, online purchase intention is affected by temperature and humidity.

• Journal of Environmental Science International
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• v.12 no.4
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• pp.399-417
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• 2003

The seasonal variation and frequency of rainfalls of Korea peninsula in Changma period show strong local weather phenomenon because of it's topographical and geographical factors in Northeast side of Asia. Based on weather entropy(statistical parameter)-the amount of average weather information-and information ratio, we can define each area's weather representativeness, which can show us more constant form included topographical and geographical factors and seasonal variation. The data used for this study are the daily precipitation and cloudiness during the recent ten years(1990-1999) at the 73 stations in Korea. To synthesize weather Entropy, information ratio of decaying tendency and half$.$decay distance, Seoul's weather representativeness has the smallest in Summer Changma period. And Puyo has the largest value in September.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.71-78
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• 2016

This paper proposes the new electric power demand forecast model which is based on an artificial neural network and considers time and weather factors. Time factors are selected by measuring the autocorrelation coefficients of load demand in summer and winter seasons. Weather factors are selected by using Pearson correlation coefficient The important weather factors are temperature and dew point because the correlation coefficients between these factors and load demand are much higher than those of the other factors such as humidities, air pressures and wind speeds. The experimental results show that the proposed model using time and seasonal weather factors improves the load demand forecasts to a great extent.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.219-224
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• 2022

The Korea Meteorological Administration(KMA) has been released life-related indexes such as 'Life industrial weather information' and 'Safety weather information' while other countries' meteorological administrations have been made 'Human-biometeorology' and 'Health meteorology' indexes that concern human sensibility effections to diverse criteria. Although human sensibility changes have been studied in psychological research criteria with diverse and innumerous application areas, there are not enough studies that make data mining based validation of sensibility change factors. In this research I made models to estimate sensibility change caused by weather factors such as temperature and humidity, and validated by collecting sensibility data from SNS text crawling and weather data from KMA public dataset. By Logistic Regression, I clarify factors affecting sensibility changes.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.397-402
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• 2013

In super-tall building construction projects, schedule risk factors which vertically change and are not found in the low and middle-rise building construction influence duration of a project by vertical attribute; and it makes hard to estimate activity or overall duration of a construction project. However, the existing duration estimating methods, that are based on quantity and productivity assuming activities of the same work item have the same risk and duration regardless of operation space, are not able to consider the schedule risk factors which change by the altitude of operation space. Therefore, in order to advance accuracy of duration estimation of super-tall building projects, the degree of changes of these risk factors according to altitude should be analyzed and incorporated into a duration estimating method. This research proposes a simulation model using Monte Carlo method for estimating activity duration incorporating schedule risk factors by weather conditions in a super-tall building. The research process is as follows. Firstly, the schedule risk factors in super-tall building are identified through literature and expert reviews, and occurrence of non-working days at high altitude by weather condition is identified as one of the critical schedule risk factors. Secondly, a calculating method of the vertical distributions of the weather factors such as temperature and wind speed is analyzed through literature reviews. Then, a probability distribution of the weather factors is developed using the weather database of the past decade. Thirdly, a simulation model and algorithms for estimating non-working days and duration of each activity is developed using Monte-Carlo method. Finally, sensitivity analysis and a case study are carried out for the validation of the proposed model.

• Journal of Forest and Environmental Science
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• v.34 no.3
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• pp.249-252
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• 2018

Climate is one of most important environmental factors on the forest ecosystem. This study was conducted to analyze the characteristics of meteorological factors in the forest area and weather stations from July 2015 to June 2016 in Cheuncheon and Hongcheon of Kangwon Province in Korea. The HOBO data logger was installed for meteorological analysis in forests area (site 1 and site 2). The meteorological data from the HOBO data logger compared with meteorological data of the weather station. The meteorological data used for the analysis was monthly mean temperature ($^{\circ}C$), monthly mean minimum temperature ($^{\circ}C$), monthly mean maximum average temperature ($^{\circ}C$), and monthly mean relative humidity (%). As a result of this study, the mean temperature ($^{\circ}C$) of forest area was relatively lower than weather station which is the outside the forest area, and the mean maximum temperature ($^{\circ}C$) of weather station was relatively higher than that of forest area. The mean relative humidity (%) was higher in forest area than weather station.

• Journal of Information Technology Applications and Management
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• v.24 no.3
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• pp.93-105
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• 2017

Demands of cosmetics are affected not only by the well-known elements such as brand, price, and customer's consumption capacity, but also by some latent factors, for example, weather and air environment. Due to complexity and dynamic changes of the above factors, their influences can hardly be estimated in an accurate way by the traditional approaches such as survey and questionnaires. Through modeling and statistical analysis of big data, this article studied the impacts of weather condition and air quality on customer flow and sales of the cosmetics distributors in China, and found several hidden influencing factors. It provided a big-data based method for the analysis of unconventional factors on cosmetics marketing in the changing weather condition and air environment.

• Fire Science and Engineering
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• v.29 no.5
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• pp.88-95
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• 2015

We propose a weather-related service for fire risk assessment in order to increase fire safety awareness in everyday life. The proposed service offers a fire risk assessment level according to weather forecasts and a degree of fire risk according to fire factors under certain weather conditions. In order to estimate the fire risk, we produced a risk matrix through data mining with a decision tree using investigation data and weather data. Through the proposed service, residents can calculate the degree of fire risk under certain weather conditions using the fire factors around them. In addition, they can choose from various solutions to reduce fire risk. In order to demonstrate the feasibility of the proposed services, we developed a system that offers the services. Whenever weather forecasting is carried out by the Korea Meteorological Administration, the system produces the fire risk assessment levels for seven major cities and nine provinces of South Korea in an online process, as well as the fire risk according to fire factors for the weather conditions in each region.

• Atmosphere
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• v.34 no.3
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• pp.273-281
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• 2024

Analyzing the information about climate change on Korean Peninsula is essential for the national defense. In this study, we used HadGEM3-RA model output (a member of CORDEX-EA) and analyzed the 3 operational weather factors (VMC, runway temperature, WBGT), which affect the aircraft field. The number of future limited days was quantitatively calculated based on the model outputs applying SSP1-2.6 and SSP5-8.5 and the operational limits of the previous three factors, and the spatial distribution, time series, and correlation of each result were analyzed. In conclusion, it was analyzed that the number of limited days by VMC would decrease, resulting from the rise in temperature and the drop in relative humidity. This means the operational environment in VMC will improve. On the other hand, the number of limited days by the runway temperature and WBGT would increase, resulting from the rise in temperature. This means the operational environment in runway temperature and WBGT will worsen.