• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2009년도 추계 학술논문 발표대회
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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.

• 한국환경과학회지
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• 제12권4호
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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.

• 전자공학회논문지
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• 제53권1호
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• pp.71-78
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• 2016

본 논문은 인공 신경망에 기반을 둔 새로운 전력 수요 예측 모델을 제시한다. 인공 신경망 입력 변수로 시간과 날씨요소를 고려하였다. 시간 요소는 하절기와 동절기 전력수요 데이터의 자기 상관계수를 측정하여 선정하였고, 날씨요소는 피어슨 상관계수를 이용하여 선정하였다. 중요한 날씨요소로는 온도와 이슬점으로 이들은 전력수요와 밀접한 상관관계를 가지고 있다. 반면에 습도, 기압, 풍속 등과 같은 날씨요소는 전력수요와의 상관관계가 높지 않게 나타나 신경망의 입력 변수에서 제외하였다. 실험결과 새로이 제안한 인공 신경망을 이용한 전력수요 모델은 시간요소 및 날씨요소와 이에 대한 가중치를 피크 전력율과 계절에 따라 차등 적용하여 높은 적중률을 보였다.

• 한국컴퓨터정보학회논문지
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• 제27권8호
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• pp.219-224
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• 2022

한국 기상청은 '생활산업 기상정보서비스'나 '위기탈출 안전날씨'와 같은 일상에 관련된 정보를 제공하고 있다. 한편, 해외에서는 독일의 '신체기상정보', 영국의 '건강 기상정보'와 같이 인간의 신체와 감성에 영향을 미치는 기상정보 역시 제공하고 있다. 비록 인간의 감성 변화가 심리학 연구 영역에서 다양하고 방대하게 이루어져 왔지만, 빅 데이터 분석 기반에 근거한 기상정보에 따른 인간의 감성 예측모형은 요원한 상태이다. 이 연구에서는 기상요소에 따른 인간의 감성변화를 예측할 수 있는 모형을 기상청의 기상 데이터셋과 SNS상 크롤링된 일자별 텍스트를 통해 개발하고 검증하고자 한다. 연구 결과 기상 요소들로 인간의 감성변화를 예측할 수 있는 모형을 만들고 검증할 수 있었으며 이는 기존 연구와 그 결을 같이한다고 볼 수 있다.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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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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• 제34권3호
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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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• 제24권3호
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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.

• 한국화재소방학회논문지
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• 제29권5호
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• pp.88-95
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• 2015

본 논문에서는 일상생활에서 화재에 대한 주민들의 경각심을 고취시킬 수 있도록 기상조건에 따른 화재위험을 평가할 수 있는 날씨 관련 서비스를 제안한다. 제안된 서비스는 기상예보에 따른 화재위험평가등급과 특정 기상조건에서 화재요인에 따른 화재위험도를 제공한다. 제안한 서비스에서는 데이터마이닝 기법인 의사결정트리를 이용하여 화재조사데이터와 관측된 기상데이터로부터 화재위험평가등급을 산출할 수 있는 화재 위험도 매트릭스를 생성한다. 주민들은 제안한 서비스를 통해 특정 기상조건에서 화재요인에 따라 화재위험도를 직접 평가할 수 있고, 화재위험도를 저감시킬 수 있는 예방책을 사용자가 선택할 수 있다. 제안한 서비스를 시스템화하여 서비스의 현실성을 확인하였다. 시스템은 온라인상에서 기상청의 기상예보가 갱신될 때마다 시도별로 기상예보에 따른 화재위험평가등급을 표시하고, 각 시도별로 해당 기상조건에서 화재요인에 따라 화재위험도를 평가할 수 있다.

• Agribusiness and Information Management
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• 제6권1호
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• pp.1-11
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• 2014

The purpose of this study is to develop the growth prediction model that can predict growth and development information influencing on the production of citrus fruits. The growth model was developed to predict the floral leaf ratio, number of fruit sets, fruit width, and overweight fruits depending on the main period of growth and development by considering the weather factors because the fruit production is influenced by weather depending on the growth and development period. To predict the outdoor-grown citrus fruit production, the investigation result for the standard farms is used as the basic data; in this study, we also understood that the influence of weather factors on the citrus fruit production based on the data from 2004 to 2013 of the outdoor-grown citrus fruit observation report in which the standard farms were targeted by the Agricultural Research Service and suggested the growth and development information prediction model with the weather information as an independent variable to build the observation model. The growth and development model for outdoor-grown citrus fruits was assumed by using the Ordinary Least Square method (OLS), and the developed growth prediction model can make a prediction in advance with the weather factors prior to the observation investigation for the citrus fruit production. To predict the growth and development information of the production of citrus fruits having a great ripple effect as a representative crop in Jeju agriculture, the prediction result regarding the production applying the weather factors depending on growth and development period could be applied usefully.

• 한국조경학회지
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• 제21권4호
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• pp.69-82
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• 1994

The purpose of this study is to estimate the probable period of the planting work in consideration of weather factors. The impact degree of weather factors on the control of planting schedule was measured by the possible working days on the basis of weather condition. To establish the weather standard, the researcher analyzed the questionnaires on the manager of planting work and also the meteorological data for 10 years(1983-1992) in Seoul. The results are as follows; $\circled1$ The possible period of the planting work is from March 17 to May 18 Spring and from September 26 to December 15 in Autumn during a year. $\circled2$ The problem working days of the planting work(106-130) days per year) are less than the building construction days(174 days per year), because of handling the living material of plants, specially in summer and winter.