• Asian-Australasian Journal of Animal Sciences
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• 제10권1호
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• pp.70-74
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• 1997

Data on 2,571 lactation records of Nili-Ravi buffaloes from four institutional herds and four field recording centers were analyzed under an animal model to see the effect of season definition on the error variance of the fitted model. Herd-year-season(HYS) was the main fixed effect along with permanent environment, breeding value and residuals as the random effects. All known relationships among the animals were considered. The error variance differed for various HYS combinations. It was minimum when then months were not grouped into seasons. The four or Five season scenarios were better than the two season scenarios. The average number of lactations represented in a HYS combination varied widely from 6 to 28. Very few subclasses for a given HYS combination warrants the use of fewer seasons for animal model evaluation of buffaloes.

• Asian-Australasian Journal of Animal Sciences
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• 제10권1호
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• pp.75-78
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• 1997

Season is very important as it defines the contemporaries for sire and cow evaluation. An attempt is made for defining season for animal model evaluation of Sahiwal animals, using 1,227 records from 730 cows. Cows were required to have a lactation length of 305-days. Ten different combinations of months for two, four, five or other seasons were tried. The other fixed effect in the model was age defined within parity. The random effects were permanent environment and animal's breeeding value along with the residual effects. A single trait animal model was used where all known relationships of an animal were incorporated in a relationship matrix. The error variance from the fitted model decreased as the number of year-season combinations increased, indicating a month-year model to be more appropriate. This, on the other hand, decreased the number of contemporaries for certain subclasses to a minimum of one, making the bull comparisons invalid. Use of a two season scenario, with winter (November through February) and summer (March through October) was better than the other combinations in terms of error variance of the fitted model and the number of lactations represented in any year-season subclass.

• 에너지공학
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• 제28권4호
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• pp.82-93
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• 2019

본 연구에서는 기존 열수요 예측 시스템이 공휴일과 같은 특정 일자의 열수요 예측율이 저하되는 문제점을 개선하기 위해 새로운 모델을 제안한다. 제안된 모델은 사계절 혼합형 신경망 모델(Four Season Mixed Heat Demand Prediction Neural Network Model)로서 열수요 예측율 상승하였고, 특히 예측일 유형별(평일/주말/공휴일) 열수요 예측율이 크게 증가하였다. 제안된 모델은 다음과 같은 과정을 통해 선정되었다. 특정 계절에 예측일 유형별로 고른 오차를 갖는 모델을 선정하여 전체 예측 모델을 구성한다. 학습 시간의 단축과 과도학습을 방지하기 위해 구조적으로 단순화된 서로 다른 4개의 모델을 각각 학습한 후에 다양한 조합을 통해 최적의 예측 오차를 보여주는 모델을 선정하였다. 모델의 출력은 예측일의 24시간의 시간대별 열수요이며 총합은 일일 총열수요이다. 이 예측값을 통해 효율적인 열공급 계획을 수립 할 수 있으며, 목적에 따라 출력값을 선택하여 활용할 수 있다. 제안된 모델의 일일 열 총수요 예측의 경우, 전체 MAPE(Mean Absolute Percentage Error, 평균 절대 비율 오차)가 개별 모델의 5.3~6.1%에서 5.2%로 향상되었고, 공휴일 열수요예측은 4.9~7.9%에서 2.9%로 크게 개선되었다. 본 연구에서는 한국 지역난방공사에서 제공한 특정 아파트 단지의 34개월 분량의(2015년 1월~ 2017년10월) 시간단위 열수요 데이터를 활용하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.118-118
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• 2020

This study investigates the change of flow characteristics over 10 Asian river basins in the past 30 years (1976-2005). The variation is estimated from The Soil and Water Assessment Tool (SWAT) model outputs based on reanalysis data which was bias-corrected for Asian monsoon reagion. The model was firstly calibrated and validated using observed data for daily streamflow. Four statistical criteria were applied to evaluate the model performance, including Coefficient of determination (R2), Nash - Sutcliffe model efficiency coeffi cient (NSE), Root mean square error-observations standard deviation ratio (RSR), and Percentage Bias (PBIAS). Then parameters of the model were applied for the historical period 1976-2005. The estimates show a temporal non-considerable increasing rate of daily streamflow in most of the basins over the past 30 years. The difference of monthly discharge becomes more significant during the months in the wet season (June to September) in all basins. The seasonal runoff shows significant difference in Summer and Autumn, when the rainfall intensity is higher. The line showing averaged runoff/rainfall ratio in all basins is sharp, presenting high variation of seasonal runoff/rainfall ratio from season to season.

• 복식문화연구
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• 제13권2호
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• pp.221-239
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• 2005

The purpose of this study was to analyse the fashion style expressed in women magazine advertisements. The method of this study was used content analysis with 692 samples in women magazines ('Woman Sense', 'Yeosung Dong-A', and 'Jubu Saeng-hwal') which were issued in March, June, September, and December from 1998 to 2002. The data analysis were divided nine elements: 1. silhouette, 2. color, 3. pattern, 4. length of skirt & slacks, 5. adjustment, 6. breadth of collar lapel, 7. shoes, 8. make-up, 9. hair style. The results of this study were as follows: 1. silhouette : The four seasons were expressed in square silhouette. 2. Color : The spring, summer, and winter seasons were expressed in white color, while the fall season was expressed in neutral color. 3. Pattern : The four seasons were expressed in plain pattern. 4. Length of skirt & slacks : The four seasons were expressed in various length. 5. Adjustment : The four seasons were expressed in single button. 6. Breadth of collar lapel : The spring, summer, and winter seasons were expressed in small breadth, while the fall season was expressed in middle breadth. 7. Shoes : The four seasons were expressed in high-heeled shoes. 8. Make-up : The four seasons were expressed in light tone. 9. Hair style : The four seasons were expressed in up-style.

• 수산경영론집
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• 제54권2호
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• pp.31-44
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• 2023

This study examines the demand system of shrimp imported from top four countries and domestically produced by using AIDS (Almost Ideal Demand System) model. Top four import countries are Vietnam, Ecuador, China, and Malaysia based on the value of imports in 2021. As results of the analysis, the demand system of shrimp turn out to be below. First, the relationship of domestic shrimp and imported shrimp (Ecuadorian and Vietnamese) is identified as complements or substitutes depending on whether the income effect is considered. This result implies that imported shrimp supplements domestic supply against excess demand while homogeneous shrimp products competes with domestic shrimp in fish market. Second, the relationship among imported shrimps turned out to be both substitutes and complements. Especially, the Vietnamese shrimp is complementary with Chinese and Malaysian shrimp, but substitutes of Ecuadorian. It is assumed that adjoining Asian countries shares similar shrimp species and processing system which differentiates from Ecuadorian. Finally, the study included quarter as dummy variable and GDP as instrumental variable of expenditure in the model. The result confirmed that domestic shrimp is highly on demand during the main production season while imported shrimp is mainly demanded during the rest of the season.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.326-326
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• 2018

The study will assess the seasonal effect of hydrological models on performance and parameters for streamflow simulation. TPHM, GR4J, CAT, and TANK-SM hydrological models will be applied for simulating streamflow in ten small and large watersheds located in South Korea. The readily available hydrometeorological data will be applied as an input to the four hydrological models and the potential evapotranspiration will be computed using the Penman-Monteith equation. The SCE-UA algorithm implemented in PEST will be used to calibrate the models considering similar objective functions bedside the calibration will be renewed to capture the seasonal effects on the model performance and parameters. The seasonal effects on the model performance and parameters will be presented after assessing the four hydrologic models results. The conventional approach and season-based results will be evaluated for each model in the tested watersheds and a conclusion will be made based on the finding of the results.

• Asian Journal of Atmospheric Environment
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• 제4권2호
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• pp.89-96
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• 2010

To identify the domains that have the greatest impacts on air quality at the surface, both the upwind and downwind areas of Seoul were determined by season using refined wind fields. Four consecutive days were selected as the study period typical of each season. The mesoscale meteorology of the study period was reproduced by using the MM5 prognostic meteorological model (PSU/NCAR Mesoscale Model) with horizontally nested grids. The gridded meteorological field, which was used on the study area of $242\;km{\times}226\;km$ with grid spacing of 2 km, was generated by using the CALMET diagnostic meteorological model. Upwind and downwind areas of Seoul were determined by calculating 24-hour backward and forward air parcel trajectories, respectively, with u, v, and w velocity vectors. The results showed that the upwind and downwind areas were extended far to the northwest and the southeast as a result of high wind speeds in the spring and winter, while they were restricted on the fringe of Seoul in the summer and fall.

• 한국의류산업학회지
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• 제23권4호
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• pp.480-490
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• 2021

Sales forecasting is crucial for many retail operations. For apparel retailers, accurate sales forecast for the next season is critical to properly manage inventory and plan their supply chains. The challenge in this increases because apparel products are always new for the next season, have numerous variations, short life cycles, long lead times, and seasonal trends. In this study, a sales forecasting model is proposed for apparel products using machine learning techniques. The sales data pertaining to outerwear items for four years were collected from a Korean sports brand and filtered with outliers. Subsequently, the data were standardized by removing the effects of exogenous variables. The sales patterns of outerwear items were clustered by applying K-means clustering, and outerwear attributes associated with the specific sales-pattern type were determined by using a decision tree classifier. Six types of sales pattern clusters were derived and classified using a hybrid model of clustering and decision tree algorithm, and finally, the relationship between outerwear attributes and sales patterns was revealed. Each sales pattern can be used to predict stock-keeping-unit-level sales based on item attributes.

• 한국수자원학회논문집
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• 제57권5호
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• pp.359-369
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• 2024

한국은 6월 21일부터 9월 20일까지를 법정홍수기로 지정하여 잠재적 홍수에 대비하여왔다. 하지만 2020년 54일의 역대 최장 장마 사례와 같이 과거와 다른 기후양상으로 인한 극한 홍수로 피해를 겪고 있다. 그동안 홍수 피해 저감을 위한 연구는 매우 많았지만, 법정홍수기가 앞으로도 유효할지에 대한 연구는 시도된 적 이 없었다. 따라서 본 연구는 21세기 관측 자료를 통해 현행 법정홍수기의 타당성을 통계적으로 검토하였으며, 이를 통해 현행 법정홍수기가 강수량 증가 추세와 지역별 강수 특성의 강화를 고려하지 못하고 있음을 확인하였다. 이러한 한계점의 해결을 위해 본 연구에서는 대상 유역에 대한 7개의 새로운 홍수기 후보군을 제안하였고, 이의 타당성을 모의 운영을 통해 분석하였다. 모의 운영 시 댐 운영룰 rigid operation method를, 댐 유입량 예측에는 long short-term memory model을 적용하였다. 제안한 홍수기 각 후보는 댐의 계획방류량과 하천의 계획홍수량을 초과하느냐를 기준으로 평가하였다. 첫 번째 기준으로 평가한 결과, 본 연구에서 제안한 홍수기 적용 시 초과 빈도와 지속시간이 각각 0.068%와 0.33% 감소되었으며, 크기 또한 24.6% 감소하였다. 두 번째 평가 기준으로 평가한 결과 역시, 홍수피해 발생 구간이 기존의 4회에서 2회로 감소하였다. 본 연구 결과를 계기로 법정홍수기 재검토가 공식적으로 이루어져 새로운 양상으로 변화하고 있는 강우 양상에 적극적으로 대비하길 기대한다.