• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.222-222
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• 2019

최근 기후변화로 인한 강우사상의 변화로 가뭄 발생 횟수와 기간이 늘어나는 추세이다. 2013~2018년 전국적으로 장기적인 가뭄이 발생함에 따라 상수도 미 급수 지역에 대한 추가 용수 공급방안을 적용하여 지역 주민의 물 이용 문제를 해결한 바 있다. 장기적으로 물 이용에 대한 갈등이 심화될 것으로 예상되는 가운데 지하수자원의 취약성에 대한 연구가 지속적으로 진행되고 있다. 기존의 연구에서는 주로 지역적인 특성을 반영할 수 있는 매개변수를 설정하고 매개변수 별가중치를 산정하여 공간적인 지하수자원 이용 취약성 평가를 실시하였다. 공간적인 취약성 평가결과는 지하수자원 이용 시기 결정 및 대체 수자원 이용 정책 결정 등 구체적인 대안을 마련하는 근거로서 한계가 있기 때문에 최근 지하수자원 이용에 대한 시간적인 취약성 평가 방법을 개발하는 연구가 진행되고 있다. 본 연구는 보다 구체적인 지하수자원 이용 시기를 결정하기 위하여 금강 유역을 대상으로 분기 별 지하수자원 이용 취약 시기 평가 방법을 개발하였다. 분기 별 지하수자원 이용 취약 시기평가 방법을 개발하기 위하여 우선 연구지역의 지하수위, 하천수위, 강수량 자료를 수집하였다. 수문 관측자료 간의 관계 분석을 통해 물 순환 측면에서의 물리적인 의미를 규명하기 위하여 강수량 자료에 한계침투량 개념을 적용한 강우이동평균 방법을 적용하였고, 하천수위 자료에 대하여 이동평균 방법을 적용하였다. 분기 단위의 지하수자원 이용 취약 시기를 평가함으로써 금강 유역의 지하수자원 이용 취약 시기를 결정하였다. 본 연구는 기존의 공간적인 취약성 평가 방법과 함께 지하수자원 이용 취약성에 대한 시공간적 분석 결과를 제공함으로써 보다 구체적인 지역 별분기 단위 지하수자원 이용 취약 시기를 결정하고, 지역 맞춤형 지하수자원 이용 및 개발 정책에 기여할 수 있을 것으로 기대된다.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.631-642
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• 2019

Many methods have been developed to solve problems found in sample surveys involving a large number of item non-responses that cause inaccuracies in estimation. However, the non-response adjustment method used under the assumption of random non-response generates a bias in cases where the response rate is affected by the variable of interest. Chung and Shin (2017) and Min and Shin (2018) proposed a method to improve the accuracy of estimation by appropriately adjusting a bias generated when the response rate is a function of the variables of interest. In this study, we studied a case where the response rate function is linear and the error of the super population model follows normal distribution. We also examined the effect of the number of stratum population on bias adjustment. The performance of the proposed estimator was examined through simulation studies and confirmed through actual data analysis.

• 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.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.980-993
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• 2020

Deep-learning based style transfer has recently attracted great attention, because it provides high quality transfer results by appropriately reflecting the high level structural characteristics of images. This paper deals with the problem of providing more stable and more diverse style transfer results of such deep-learning based style transfer method. Based on the investigation of the experimental results from the wide range of hyper-parameter settings, this paper defines the problem of the stability and the diversity of the style transfer, and proposes a partial loss normalization method to solve the problem. The style transfer using the proposed normalization method not only gives the stability on the control of the degree of style reflection, regardless of the input image characteristics, but also presents the diversity of style transfer results, unlike the existing method, at controlling the weight of the partial style loss, and provides the stability on the difference in resolution of the input image.

• Journal of Environmental Impact Assessment
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• v.31 no.4
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• pp.265-270
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• 2022

With the implementation of the fox restoration project, the number of foxes released into nature are increasing; therefore, in the future, foxes will be dispersed to other areas and will appear in human habitats. In this study, the habitat suitability index (HSI) of foxes was developed to predict and prepare for the effects. After extracting major environmental variables through literature research and GIS analysis, 5 suitability indices (SIs) were constructed. The forest physiognomy, slope, aspect, distance from water source, and distance from road are the main variables, and the arithmetic average value by giving twice the weight to the forest physiognomy is the HSI result. As a result of comparing with the data from the Natural Environment Survey, it is found that the fox coordinates have an average HSI value of 0.64, and the probability of appearance is high when it is 0.53 or higher. Using the results of this study, it is expected to be able to predict the distribution of foxes in advance, to use them as basic data for future restoration plans, or to identify the distribution of the species and the reduction plan in future environmental impact assessments.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.139-147
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• 2022

This study tried to analyze the relationship among physical activity level, subjective health status, COVID-19 Fear. This study used the 2020 Community Health Survey that includes 229,269 survey data from adults over 19 years old. The complex sampling design was applied including weight, stratification, cluster variables. Through the SPSS statistics program with complex sampling frequency analysis, complex sampling Chi-square and complex sampling regression, this study found followings. First, the group with high level of physical activity showed higher level of subjective health status than the group with low level of physical activity. Second, the group with high level of physical activity showed lower level of COVID-19 fear than the group with low level of physical activity. Third, the group with high level of subjective health status showed lower level of COVID-19 fear than the group with low level of subjective health status. However, this study has the limitation that this study did not check whether participant is diagnosed with Covid-19 or not.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.57-69
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• 2022

Even though demand to charge EV(electric vehicles) is increasing, there are some problems to construct EV charging stations and problems from deficient them. Typical problem of EV charging stations is discordance for EV charging station location with its demand. This study investigates methods to determine the optimized location for fast EV charging stations considering charging demand in Seoul. Firstly, variables influencing on determination of determine the optimized location for fast EV charging stations were decided, and then evaluation of weights of the variables and data collection were conducted. Using the weights, location potential scores for each area-cell were calculated and optimized locations for fast EV charging stations were resulted.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.155-155
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• 2020

최근 전 세계적으로 기후변화 및 이상기후로 인해 홍수, 가뭄과 같은 수자원과 관련된 재해들의 빈도가 증가하고 있는 추세이다. 가뭄은 발생 시작 및 종료 시기가 명확하지 않고, 그 피해가 광범위한 특징으로 인해 농업분야에 직접적인 피해를 주고 있으며, 농산물 생산성 및 안정적인 농업용수 확보에 큰 영향을 미치고 있다. 과거 가뭄을 해석하기 위해서는 일반적으로 강수량, 가뭄지수 등 단일지표를 활용하여 가뭄을 평가하였으나, 최근 선제적인 가뭄대응을 위해 다양한 인자들을 종합하여 판단하는 취약성 평가 (Vulnerability Assessment) 개념을 도입하였다. 농업가뭄 취약성은 IPCC (Intergovernmental Panel on Climate Change)에서 기상 및 수문학적 가뭄에 의한 작물 생산 피해 및 가축의 피해를 동반할 수 있는 가능성으로 정의한다. 본 연구에서는 농업용 저수지 중심의 농업용수 기반 취약성 평가 항목을 선정하여 농업가뭄 취약지도를 작성하였다. 민감도, 노출도 및 적응능력 개념에 적합한 대응변수를 활용하여 저수지의 저수율, 용수 부족 및 가뭄 대응능력 뿐만 아니라 사회·환경적, 기상학적 영향을 고려한 평가 항목 선정하였다. 항목별 단위 및 특성을 통합하기 위해 스케일 재조정 (Re-Scaling), Z-Score 등 다양한 방법을 활용하여 표준화를 실시하였으며, AHP (Analytic Hierarchy Process), 엔트로피 분석 등을 통해 항목별 가중치를 산정하였다. 또한 농업가뭄에 긍정적인 영향과 부정적인 영향을 미치는 항목을 구분하여 대응변수를 적용하였다. 이를 바탕으로 농업가뭄 취약성을 평가하여 항목별 등급을 구분하였으며, 전국 167개 시군을 대상으로 농업가뭄 취약지도를 작성하였다. 본 연구의 결과는 시군별 맞춤형 농업가뭄 대응정책의 기초자료 활용 가능하며, 농업가뭄 취약지역/상습가뭄지역에 대한 정보 제공이 가능할 것으로 판단된다.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.949-959
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• 2012

This article is to find the right size of decision trees that performs better for boosting algorithm. First we defined the tree size D as the depth of a decision tree. Then we compared the performance of boosting algorithm with different tree sizes in the experiment. Although it is an usual practice to set the tree size in boosting algorithm to be small, we figured out that the choice of D has a significant influence on the performance of boosting algorithm. Furthermore, we found out that the tree size D need to be sufficiently large for some dataset. The experiment result shows that there exists an optimal D for each dataset and choosing the right size D is important in improving the performance of boosting. We also tried to find the model for estimating the right size D suitable for boosting algorithm, using variables that can explain the nature of a given dataset. The suggested model reveals that the optimal tree size D for a given dataset can be estimated by the error rate of stump tree, the number of classes, the depth of a single tree, and the gini impurity.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.59-77
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• 2003

This study is to validate the use of macro language for the land suitability analysis aiming to help to resolve land use conflicts. The silver-town suitability analysis is conducted on the Geejang Gun, Busan Metropolitan city. Such digital maps as terrain, road, facility, and water body were created for various cartographic models. A cartographic model identified the best suitable areas for silver-town development based on the such site selection variables as a distance to facility and road, slope and aspect of terrain, land use etc. Then, the other cartographic model identified the most favorable site among the candidate sites based on the comparison of the aspect of proximity, usage and environmental quality. Macro language was used for these modeling process and was used for the manipulation of all these spatial variables used in the models to resolve land use conflicts relating to the decision making process of the final site selection. This study will improve the effectiveness and rationality of the traditional site suitability analysis.