• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.387-387
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• 2019

우리나라는 최근 10년간 자연재난 중 호우로 인해 인명피해 약 120명, 재산피해 약 1조 4천억원을 기록하였으며, 또한 기후변화로 인해 강한 국지성 집중호우의 발생빈도가 높아질 것으로 예상됨에 따라 호우에 의한 침수피해가 증가될 것으로 예상된다. 특히 본 연구 대상지역인 인천시의 경우 도시화로 인해 인구밀도 및 불투수지역이 증가함에 따라 침수피해가 대형화되고 있는 실정이다. 이에 본 연구에서는 인천시와 같은 도심지역에서의 침수발생을 사전에 예측하고 침수발생에 대한 대비 대응을 위해 하수관망 해석을 위한 SWMM 모델과 침수해석을 위한 2DIS 모델을 연계하여 인천시 침수심 생산체계를 구축하고자 한다. 본 연구에 적용한 침수심 생산과정은 크게 강우자료 생산, 유역 및 하수관망 해석, 침수 해석 등 총 3단계 과정으로 구성된다. 강우자료 생산과정에서는 유역 및 하수관망 해석과 침수 해석을 위한 10분 단위 유역평균 강우량자료를 생산한다. 유역 및 하수관망 해석과정에서는 지형자료 및 강우자료를 이용하여 SWMM 모델을 통해 맨홀에서의 월류량 자료를 생산한다. 마지막으로 침수해석과정에서는 지형자료와 함께 앞서 두 과정을 통해 생산된 강우 및 맨홀 월류량 자료를 입력자료로 하여 2DIS 모델을 통해 10분 단위의 시계열 침수심 정보 및 격자별 최대 침수심정보를 생산한다. 본 연구에서의 공간해상도는 도심지역의 도로단위 고해상도 침수심 정보 생산을 위해 6m 단위로 하였으며, 시간해상도는 단시간에 발생하는 도심지역의 침수특성 반영을 위해 10분으로 하였다. 또한, 침수발생 시 발생한 강우의 지표흐름 영향을 반영하기 위해 빗물받이효율 변화에 다른 침수심을 분석하였다. 본 연구를 통해 도출된 모의 침수심 결과를 실제 침수피해사례 및 풍수해저감종합계획 결과와 비교하였으며, 다수 지역에서 실제 침수발생지역과 동일하게 침수가 발생한 것으로 나타났다. 또한, 전체적인 침수 양상이 유사하게 발생함을 확인하였다. 향후 관측자료를 이용한 하수관망 및 침수해석 모델의 최적화, 하천유량 예측을 통한 하류 기점수위의 반영 등을 통해 정확도를 개선할 수 있을 것으로 판단되며, 이를 통해 인천시 침수발생을 사전에 예측하여 침수피해에 대비 및 대응과 침수피해 발생 시 정확하고 상세한 원인 분석 및 예측이 가능할 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.268-268
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• 2023

전 지구적 급격한 기후변화로 인해 수문기상인자들의 비선형적 변동성이 발생함과 동시에 가뭄, 홍수와 같은 수재해의 발생빈도 및 강도가 증가하고 있는 추세이다. 이에 따라, 세계의 유수기관 (NASA, ESA 등)에서는 대기모형과 해양 모형의 결합 및 수치해석적 접근법을 활용하여 계절내-계절 (Subseasonal to seasonal; S2S) 예측치를 생산하여 제공하고 있다. 이에 따라, 본 연구에서는 European Centre for Medium-Range Weather Forecast (ECMWF)에서 산정되는 수문기상인자 (강수량, 증발산량 및 유출량)에 대한 정확도를 평가하고자 한다. 연구지역으로는 다양한 기후대 및 토지 피복으로 구성되어 있으며, El-Nino-Southern Oscillation (ENSO), Indian Ocean Diapole (IOD)와 같은 기후 현상이 빈번히 발생하는 호주지역을 대상으로 연구를 수행하였다. ECMWF S2S 자료에 대한 통계적 검증은 1) 지점 기반 관측치와 더불어 2) 물수지 모델 기반 수문 추정치 (The Australian Water Resources Assessment Landscape Model; AWRA-L)와 비교하였다. 연구 결과 S2S 강우 및 증발산량 산정치의 경우 비교적 짧은 예측기간(약 2주)에서 상대적으로 높은 상관관계 (R=0.5~0.6)와 낮은 편차 (강수량 = 0.10 mm/day, 증발산량 = 0.21 mm/day)를 나타내었다. 유출량의 경우, 강우 및 증발산량에 비해 상대적으로 낮은 정확도를 나타내었으며, 예측 기간이 길어짐에 따라 불확실성이 상당히 높아지는 것으로 확인되었다. 이는, S2S 계산과정에서 강우 및 증발산량 뿐만아니라 지표 유출로 도달하기 전까지의 수문기상인자들의 불확실성이 모두 모여 유출량의 불확실성이 높아진 것으로 확인할 수 있었다. 계절적 검증에서는, 강우 및 증발산량 모두 여름철에 높은 상관관계를 나타내었지만 불확실성은 상대적으로 큰 값을 나타내었다. 자세한 분석을 위해, 공간적인 불확실성을 분석해본 결과 ECMWF S2S가 매우 습윤하거나 건조한 지역에서 수문기상인자를 예측하는데 있어 한계성이 나타난 것을 확인하였다. 본 연구를 토대로, 추후 S2S 예측치에 대한 보정과 더불어 미래의 수재해 발생 위험도에 대한 정보를 획득하는데 적용될 수 있을 것으로 판단된다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.374-390
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• 2021

Growth and yield of field vegetable crops would be affected by climate conditions, which cause a relatively large fluctuation in crop production and consumer price over years. The yield prediction system for these crops would support decision-making on policies to manage supply and demands. The objectives of this study were to compile literatures related to onion and garlic and to perform data-mining analysis, which would shed lights on the development of crop models for these major field vegetable crops in Korea. The literatures on crop growth and yield were collected from the databases operated by Research Information Sharing Service, National Science & Technology Information Service and SCOPUS. The keywords were chosen to retrieve research outcomes related to crop growth and yield of onion and garlic. These literatures were analyzed using text mining approaches including word cloud and semantic networks. It was found that the number of publications was considerably less for the field vegetable crops compared with rice. Still, specific patterns between previous research outcomes were identified using the text mining methods. For example, climate change and remote sensing were major topics of interest for growth and yield of onion and garlic. The impact of temperature and irrigation on crop growth was also assessed in the previous studies. It was also found that yield of onion and garlic would be affected by both environment and crop management conditions including sowing time, variety, seed treatment method, irrigation interval, fertilization amount and fertilizer composition. For meteorological conditions, temperature, precipitation, solar radiation and humidity were found to be the major factors in the literatures. These indicate that crop models need to take into account both environmental and crop management practices for reliable prediction of crop yield.

• Economic Analysis
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• v.24 no.3
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• pp.1-36
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• 2018

When it comes to explaining the relationship between inventory investment and business fluctuations, the production smoothing theory and the stock-out avoidance theory take contradictory stances. Decision-making related to inventory investments of corporations is thought to be influenced by both motives, but the relative sizes or directions of their respective influences can differ depending upon the phase of the business cycle. Against this backdrop, this paper differs from existing studies in that it theoretically tests the relative significances of the production smoothing and stock-out avoidance motives in the inventory investment dynamics, while placing its analytical focus on determining the existence and patterns of the asymmetric dynamics of inventory investment over the business cycle phases. To this end this paper sets up a non-linear model that is expanded from the existing linear inventory investment model, and checks whether its predictive power is better than that of the existing model. The results of analysis confirm the nature of the asymmetric dynamics of inventory investment over the business cycle phases. A stock-out avoidance motive appears but there is no significant production smoothing motive in boom times. In downturns, in contrast, the stock-out avoidance motive is insignificant, but a quality of asymmetric dynamics in which changes in inventory cause the deepening of recessions, due to the non-convexity of production costs proposed by Ramey (1991), is detected. This paper confirms that a model considering the asymmetric dynamics of inventory investment can have better predictive power than one that does not consider it, through within-sample and out-of-sample predictions and various predictive power tests. These research results are expected to be useful for economic forecasting, through their enhancement of the understandings of the inventory investment dynamics and of the nature of its business cycle destabilization.

• Environmental and Resource Economics Review
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• v.24 no.4
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• pp.727-745
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• 2015

This paper analyzes the firms' optimization behavior in response to rising demand for non-priced renewable energy in the manufacturing industries by using an input distance function. The annual estimates of the shadow price of renewable energy is derived and the trend of its shadow price over time is analyzed. The degree of substitution of renewable energy for fossil-fuels is examined. The input-based Malmquist productivity index, defined as a composite of the technical efficiency and technical change measures, is measured. The contribution of renewable energy input growth to the Malmquist index is analyzed. Empirical results indicate that the shadow price of renewable energy declined at an average annual rate of 17% over the period 1992-2012. Substitutability between renewable energy and fossil-fuels was limited. On average, a 1% increase in renewable energy would decrease Malmquist index by 0.04% per year.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.1-4
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• 2004

This paper identifies defects to produce a reliable software and analyzes the relationship between defects. Also, this paper is intended to develop the relationship between defects and their causes to introduce. For the doing, first, to meet to customer satisfaction and make flexibility and productivity and second. to maximize market extension and financial outcome by controlling of quality and delivery.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.427-432
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• 2004

As it is keen competition of a construction market and the recognition that increases construction productivity for maintaining competitiveness, it is increased importance of an interest about productivity and efficiency in the construction industry. This study measures productivity through the instance of investigation that the existing productivity measurement method was utilized and presented a work improvement matter based on the measured contents. The proposed improvement matter is verified through a simulation technique. The purpose of this paper is for a field supervisor to have presented the way that a selection does the most suitable work method to be suitable for a situation, and can forecast production, though a simulation technique is not the most alternative that considered field condition in analyzing productivity measurement.

• Korean Journal of Construction Engineering and Management
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• v.15 no.3
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• pp.38-46
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• 2014

The Global's top five Design Firms selected from BauNetz a German architectural magazine in 2007 designed free form building design which was 25% of the overall design by 2006-2010. Free form building is a landmark of the city and the country so its social and economic impacts are very large. In case of Korea, free form buildings such as Tribowl in Incheon, KINTEX Exhibition hall 2 and Dongdaemun Design Plaza have increased. However, those the increase in design trends and, the needs due to the lack of free form building design and construction management experience, free form building projects can't be expected to profitability and have a number of problems after completion. Especially, there are many excessive quality problems and the rising cost due to design changes frequently and lack of experience and data. Thus an initial plan regardless of considering of free form building's characteristics can be a huge risk because of the difference with the plan and actual projects, yet there aren't free form building project's performance data and case studies related to productivity. In this study, through selection of low-construction productivity works and an analysis of the work process and productivity data, hope to propose an actual field productivity of free form building and the ways to improve productivity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1560-1566
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• 2017

Recently, accumulation of data on pig farm is enabled through the wide spread of smart pig farm equipped with Internet-of-Things based sensors, and various machine learning algorithms are applied on the data in order to improve the productivity of pig farm. Herein, multiple machine learning schemes are used to predict the water usage in pig farm which is known to be one of the most important element in pig farm management. Especially, regression algorithms, which are linear regression, regression tree and AdaBoost regression, and classification algorithms which are logistic classification, decision tree and support vector machine, are applied to derive a prediction scheme which forecast the water usage based on the temperature and humidity of pig farm. Through performance evaluation, we find that the water usage can be predicted with high accuracy. The proposed scheme can be used to detect the malfunction of water system which prevents the death of pigs and reduces the loss of pig farm.

• Proceedings of the KAIS Fall Conference
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• 2004.11a
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• pp.77-79
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• 2004

Optical Disc(DVD) 생산 공정에 있어서 생산 효율성을 극대화하는데 많은 어려움이 존재한다. 최적공정 변수를 예측하기가 어렵기 때문에, 사출 성형 공정 시 발생하는 여러 가지 불량에 대한 체계적인 기술이 정립이 되지 않고 있는 실정이다. 본 연구는 Optical Disc 생산 시 요구되는 일반적인 사항들을 고찰하고, 불량품을 최소화하기 위한 여러 가지 사례연구 및 분석을 통하여 얻어진 지식을 바탕으로 문제 해결을 위한 지능형 시스템을 개발하였다.