• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.656-659
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• 2017

현대 사회에서는 다양한 이동수단 중 지하철, 버스 등의 대중교통에 대한 수요가 높은 편이다. 본 연구의 배경이 되는 서울특별시의 경우에는 출퇴근 시, 과반 수 이상이 대중교통을 이용한다. 대중교통 이용량에는 날씨, 평일-주말, 연착, 도로현황 등 여러 가지에 원인을 둔다. 본 연구에서는 여러 요인 중에서도 날씨 데이터(기온, 강수량, 미세먼지)에 초점을 두어, 날씨에 따른 대중교통 이용량의 변화양상을 학습하여 예측하는 연구를 진행한다. 서울특별시 25개 자치구마다의 날씨 데이터와 대중교통 이용 데이터를 이용하여 Regression을 통한 데이터 학습을 진행하였으며, 학습된 모델을 통한 날씨에 따른 서울특별시 대중교통 이용량 예측에 따른 평균 오차율은 15.49%로 낮은 오차율을 가진다. 본 연구 결과는 날씨에 따른 버스와 지하철의 배차 간격 조절 등의 대중교통 배치 판단 결정에 기초자료로 사용될 것으로 기대된다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.37-38
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• 2022

농산물의 산지 가격이나 도매가격이 등락하면, 즉시 또는 일정한 시차 이후에 소비자가격도 등락한다. 본 논문에서는 선형회귀모델을 통해 쌀 가격을 예측하고 쌀 가격에 영향을 미치는 날씨의 시기를 찾아보고자 한다. 이에 따라 KAMIS, 기상자료개방포털, KOSIS에서 수집한 날씨, 생산량, 그리고 소비자물가 등락률 데이터를 이용하여 쌀 가격 예측을 수행하고, 날씨 데이터와 쌀 가격 데이터의 날짜 간격을 두어 날씨가 쌀 가격에 영향을 미치는 시기를 알아보았다. 모델 평가 결과, 2개월 간격을 두고 예측한 RMSE가 164.135로 가장 큰 영향을 미쳤다. 본 연구를 기반으로 향후 다른 농산물의 가격 예측도 가능할 것이며 농산물에 영향을 미치는 변수의 시기도 예측할 수 있을 것으로 기대한다.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2933-2940
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• 2018

It is known that fruit is more affected by the weather than other crops. Therefore, in order to create high value for farmers, it is necessary to develop a wholesale price model considering the weather. Peaches produced under relatively limited conditions were chosen as subjects of study. The data were collected from 2015 to 2017 provided by okdab 4.0. The meteorological data used for the analysis were generated by weighting the cultivation area and the variables with high correlation among the weather data were selected from the day before to 7 days before. Randomforest, gradient boosting machine, and XGboost were used for the analysis. As a result of analysis, XGboost showed the best performance in the sense of RMSE and correlation, and price prediction was comparatively well predicted, but the accuracy of the trading volume prediction was not so good enough. The top three weather variables affecting to the peach were minimum temperature, average maximum temperature, and precipitation.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.413-420
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• 2013

Stochastic weather generator is a commonly used tool to simulate daily weather time series. Recently, a generalized linear model(GLM) has been proposed as a convenient approach to tting these weather generators. In the present paper, a stochastic weather generator is considered to model the time series of daily temperatures for Seoul South Korea. As a covariate, precipitation occurrence is introduced to a relate short-term predictor to short-term predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate a time series of seasonal mean temperatures in the GLM weather generator as a covariate.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.519-521
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• 2022

본 논문에서는 교통약자들의 이동제한 및 한계와 코로나 19로 인한 관광산업의 손실을 해결할 VR/360도 가상현실을 통한 웹 플랫폼 개발을 제안한다. 이 연구는 활용될 자원인 계절과 날씨자료를 효율적으로 촬영 및 준비하여 기존의 VR/360도의 가상현실을 최대화하고, 기존의 로드뷰 API 및 VR기기의 응용을 다양화한다. 또한, 이 연구는 '관광지를 방문한다'라는 개념을 실외뿐만이 아니라 실내에서도 사실적으로 체험할 수 있음을 제시한다. 이때 사실적인 체험을 더욱 극대화하기 위하여 VR/360도에 접목된 계절과 날씨의 콘텐츠를 구매할 수 있게 하여 소비자에게 선택지 내에서의 다양성을 주고, 단순 체험이 아닌 관광산업의 경제적 이윤으로 연결한다. 본 논문에서는 예상결과를 통하여 기존의 단순 VR/360도 체험을 통한 가상현실에 비해 좀 더 다양한 환경 조성을 통한 콘텐츠와 관광산업의 개선 및 경제성 면에서 발전성을 보인다.

• Smart Media Journal
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• v.6 no.2
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• pp.50-56
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• 2017

Due to new social environment, expenditure on eating out has increased over the last few year, thereafter the food-tech industries have steadily grown as well. We have studied what variable would affect customer's choices when they plan to eat out or order in. There are two variables are taken into account to prove it. Firstly, it is climate changes, such as an amount of rainfall, snowfall and clouds. Secondly, it is days, such as seasons and holidays. Based on this, we looked up the SikSin user's behaviors patterns, then did analysis of the daily data provided by the Meteorological office. By the end of the study, it turned out that two variables, climate changes and days, both have a strong influence on customer's choices. It is considered that this research outcome will make contributions to small businesses founders who want to take the initiative, marketing managers and people who are engaged in the food-tech industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.56-65
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• 2019

This study empirically analyzes the effect of weather on pedestrian volume in an urban space. We used data from the 2009 Seoul Flow Population Survey and constructed a model with the pedestrian volume as a dependent variable and the weather and physical environment as independent variables. We constructed 28 models and compared the results to determine the effects of weather on pedestrian volume by season, land use, and time zone. A negative binomial regression model was used because the dependent variable did not have a normal distribution. The results show that weather affects the volume of walking. Rain reduced walking volume in most models, and snow and thunderstorms reduced the volume in a small number of models. The effects of the weather depended on the season and land use, and the effects of environmental factors depended on the season. The results have various policy implications. First, it is necessary to provide semi-outdoor urban spaces that can cope with snow or rain. Second, it is necessary to have different policies to encourage walking for each season.

• Journal of the Korean Geographical Society
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• v.39 no.1
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• pp.13-26
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• 2004

This paper examined the possibility of NET application for a relative weather stress index in Korea. The characteristic of NET distribution used temperature, relative humidity, wind speed which forecasting at Korean Meteorological Administration were analyzed. Regional critical values of daily maximum NET of stress index for summer resembled the distribution of daily maximum temperature because were not impacted wind and humidity but temperature. Regional critical values of daily minimum NET of stress index for winter distributed variously compared with summer. The highland region and the northern region of Seoul were impacted of low temperature and coastal region which strong wind. The occurrences of stressful days did not vary in summer, but obviously increased in winter after mid-1990s.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.475-485
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• 2014

A stochastic weather generator based on a generalized linear model (GLM) approach is a commonly used tools to simulate a time series of daily weather. In this paper, we propose a multi-site weather generator with applications to historical data in South Korea. The proposed method extends the approach of Kim et al. (2012) by considering spatial dependence in the model. To reduce this phenomenon, we also incorporate a time series of seasonal mean precipitations of South Korea in the GLM weather generator as a covariate. Spatial dependence was incorporated into the model through a latent Gaussian process. We apply the proposed model to precipitation data provided by 62 stations in Korea from 1973{2011.

• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.38-41
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• 2001

본 연구는 2000년 9월4일 Landsat ETM+ 위성화상자료에 기초하여 산출된 연무지수(haze index)를 서울시 구별로 비교, 분석하였다. 태슬모자형 변환(Tesseled Cap transformation)의 제 4특징인 연무지수를 산출하기 위해 6개의 계수를 새로 구하였다. 시정거리가 21.5km인 비교적 좋은 날씨상태에서 강남구와 서초구의 경우 다른 구에 비해 월등히 연무지수가 높게 나타났다. 그리고 강북지역의 연무지수는 강남지역보다 낮다. 비교적 높은 연무지수를 갖는 강북지역의 구는 용산구, 종로구, 노원구이다.