• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2022년도 학술발표회
• /
• pp.142-142
• /
• 2022

Adjusting weather radar data is a prerequisite for its use in various hydrological studies. Effect of spatial variables are considered to adjust weather radar data in many of these researches. The existence of diverse topography in South Korea has increased the importance of analyzing these variables. In this study, some spatial variable like slope, elevation, aspect, distance from the sea, plan and profile curvature was considered. To investigate different topographic conditions, tried to use three radar station of Gwanaksan, Gwangdeoksan and Gudeoksan which are located in northwest, north and southeast of South Korea, respectively. To form the suitable fuzzy model and create the best membership functions of variables, ANFIS-PSO model was applied. After optimizing the model, the correlation coefficient and sensitivity of adjusted Quantitative Precipitation Estimation (QPE) based on spatial variables was calculated to find how variables work in adjusted QPE process. The results showed that the variable of elevation causes the most change in rainfall and consequently in the adjustment of radar data in model. Accordingly, the sensitivity ratio calculated for variables shows that with increasing rainfall duration, the effects of these variables on rainfall adjustment increase. The approach of this study, due to the simplicity and accuracy of this method, can be used to adjust the weather radar data and other required models.

• Advances in Computational Design
• /
• 제4권1호
• /
• pp.15-32
• /
• 2019

One of the efficient and useful tools to achieve the optimal design of structures is employing the sensitivity analysis in the finite element model. In the numerical optimization process, often the semi-analytical method is used for estimation of derivatives of the objective function with respect to design variables. Numerical methods for calculation of sensitivities are susceptible to the step size in design parameters perturbation and this is one of the great disadvantages of these methods. This article uses complex variables method to calculate the sensitivity analysis and combine it with discrete sensitivity analysis. Finally, it provides a new method to obtain the sensitivity analysis for linear structures. The use of complex variables method for sensitivity analysis has several advantages compared to other numerical methods. Implementing the finite element to calculate first derivatives of sensitivity using this method has no complexity and only requires the change in finite element meshing in the imaginary axis. This means that the real value of coordinates does not change. Second, this method has the lower dependency on the step size. In this research, the process of sensitivity analysis calculation using a finite element model based on complex variables is explained for linear problems, and some examples that have known analytical solution are solved. Results obtained by using the presented method in comparison with exact solution and also finite difference method indicate the excellent efficiency of the proposed method, and it can predict the sustainable and accurate results with the several different step sizes, despite low dependence on step size.

• Journal of the Korean Data and Information Science Society
• /
• 제27권4호
• /
• pp.969-977
• /
• 2016

야외에서 재배되는 주요 채소류의 생산에 대한 기상변화의 영향력이 점차 커지고 있다. 기상변화로 인한 농작물 생산량의 변화는 공급과 수요의 불안정과 물가안정의 불안요소로 작용하고 있다. 본 논문에서는 패널회귀모형을 이용하여 기상상태에 따른 마늘의 생산량을 추정하였다. 2006년부터 2015년까지의 마늘 주산지 15곳의 10a당 마늘 생산량과 해당 지역의 기상자료를 사용하였다. 7가지 기상요인 (평균기온, 평균최저기온, 평균최고기온, 누적강수량, 누적일조시간, 평균상대습도, 평균지면온도)의 월별 (1월-12월)자료인 총 84개 기상변수중 다중회귀분석 단계선택방법을 통하여 7가지 기상변수를 선택하여 패널회귀모형에 사용하였다. 고정효과 모형과 확률효과 모형을 구분하는 하우스만 검정을 통하여 확률효과 모형으로 분석한 결과 평균최고기온 (1월), 누적강수량 (3월, 10월), 누적일조시간 (4월, 10월)등이 마늘 생산량 추정에 유의한 변수로 나타났다. 또한 연도별로 추정된 생산량 추정값의 추이가 실제 생산량과 동일한 추세를 보이고 있어 제안된 패널 회귀 모형이 잘 적합됨을 확인할 수 있다.

• Nutrition Research and Practice
• /
• 제15권sup1호
• /
• pp.53-69
• /
• 2021

BACKGROUND/OBJECTIVES: To determine the weight change trend among the adult Turkish population after 1 yr of the coronavirus disease 2019 (COVID-19) pandemic and factors associated with weight change. MATERIALS/METHODS: This cross-sectional study was conducted between 26 February and 6 March 2021 using an online questionnaire that included questions for sociodemographic variables, eating habits, stress level, and the Three-Factor Eating Questionnaire-R18. Those who weighed themselves 1-2 weeks before the pandemic was declared in Turkey and remembered their weight were invited to participate in the study. Trends in weight and body mass index (BMI) change were calculated. The variables associated with a 1% change in BMI were assessed using hierarchical regression analysis. RESULTS: The study was conducted with 1,630 adults (70.25% female) with a mean age of 32.09 (11.62) yrs. The trend of weight change was found to increase by an average of 1.15 ± 6.10 kg (female +0.72 ± 5.51, male +2.16 ± 7.22 kg) for the first year of the COVID-19 pandemic. The rate of participants with a normal BMI (18.50-24.99 kg/m²) decreased to 51.91% from 55.75%. Consuming an "Increased amount of food compared to before the pandemic" was found to be the independent variable that had the strongest association with a 1% increase in BMI (β = 0.23 P < 0.001). The average change in the BMI was higher in older individuals than in those who were younger. A high stress level was associated with a decrease in BMI (β = -0.04 P = 0.048). CONCLUSIONS: In this study, the factors associated with weight change after 1 yr of the pandemic in the Turkish population was reported for the first time. A high stress level and increased weight gain trend still occur in Turkey after 1 yr of the pandemic.

• 한국정밀공학회지
• /
• 제17권2호
• /
• pp.80-88
• /
• 2000

This paper presents a method to optimize the bump steer characteristics (the change of toe angle with vertical wheel travel) with respect to hard points in the double wishbone front suspension of the four-wheel-drive vehicle using the design of experiment, multibody dynamics simulation, and optimum design program. Front and rear suspensions are modeled as the interconnection of rigid bodies by kinematic joints and force elements using DADS. The design variables with respect to the kinematic characteristics are obtained through the experimental design sensitivity analysis. An object function is defined as the area of absolute differences between the desired and experimental toe angle. By the design of experiment and regression analysis, the regression model function of bump steer characteristics is extracted. The design variables that make the toe angle optimized are selected using the optimum design program DOT. The lane change simulations and tests of the full vehicle models are implemented to evaluate the improvement of vehicle handling performances by the optimization of front bump steer characteristics. The results of the lane change simulations show that the vehicle with optimized bump steer has the weaker understeer tendency than the vehicle with initial bump steer.

• Ocean and Polar Research
• /
• 제36권4호
• /
• pp.327-341
• /
• 2014

This study aims to analyze causality among Wando abalone producer prices by size using a vector autoregressive model to expiscate the leading-price of Wando abalone in various price classes by size per kg. This study, using an analytical approach, applies a unit-root test for stability of data, a Granger causality test to learn about interaction among price classes by size for Wando abalone, and a vector autoregressive model to estimate the statistical impact among t-1 variables used in the model. As a result of our leading-price analysis of Wando abalone producer prices by shell size using a VAR model, first, DF, PP, and KPSS tests showed that the Wando abalone monthly price change rate by size differentiated by logarithm were stable. Second, the Granger causality relationship analysis showed that the price change rate for big size abalone weakly led the price change rate for the small and medium sizes of abalone. Third, the vector autoregressive model showed that three price change rates of t-1 period variables statistically, significantly impacted price change rates of own size and other sizes in t period. Fourth, the impulse response analysis indicated that the impulse responses of structural shocks for price change rate for big size abalone was relatively more powerful in its own size and in other sizes than shocks emanating from other sizes. Fifth, the variance decomposition analysis indicated that the price change rate for big size abalone was relatively more influential than the price change rates for medium and small size abalone.

• 한국농림기상학회지
• /
• 제25권4호
• /
• pp.404-414
• /
• 2023

본 연구에서는 미래 SSP 기후변화 시나리오 자료를 생산하기 위해 과거 30년(1981-2010)에 대한 한반도 농업용 전자기후도를 생산하고 평가하였다. ERA5 재분석 자료와 기상청 ASOS 자료에 지형인자를 고려하는 IGISRM 통계 모형을 이용하여 기후요소 6종(강수량, 평균기온, 최고기온, 최저기온 풍속, 상대습도, 일사량)에 대한 1km 해상도의 격자형 상세자료를 생산하였다. 연 평균(누적) 분포도를 살펴본 결과, 모든 변수는 기상청 ASOS 관측에서 나타난 일반적인 특성을 잘 모의하면서 지형적 효과가 적절하게 반영되었다. 농진청 농업기상 AWS와 기상청 방재기상 AWS를 이용하여 상관계수, Slope, NRMSE를 계산한 결과, 기온관련 변수에서는 재현성이 우수하게 나타났으며, 그 외 변수에서는 재현성이 다소 낮고 지역적 편차가 큰 것으로 나타났다. 관측정보 기반의 농업용 전자기후도는 미래 SSP 기후변화 시나리오 자료를 상세화하는데 기본 자료로 활용될 것이다.

• 한국농공학회논문집
• /
• 제61권4호
• /
• pp.75-86
• /
• 2019

Recently, natural disasters due to abnormal climates are frequently outbreaking, and there is rapid increase of damage to aged agricultural infrastructure. As agricultural infrastructure facilities are in contact with water throughout the year and the number of them is significant, it is important to build a maintenance management system. Especially, the current maintenance management system of pumping and drainage stations among the agricultural facilities has the limit of lack of objectivity and management personnel. The purpose of this study is to develop a performance evaluation model using the factors related to performance degradation of pumping and drainage facilities and to predict the performance of the facilities in response to climate change. In this study, we focused on the pumping and drainage stations belonging to each climatic zone separated by the Korea geographical climatic classification system. The performance evaluation model was developed using three different statistical models of POLS, RE, and LASSO. As the result of analysis of statistical models, LASSO was selected for the performance evaluation model as it solved the multicollinearity problem between variables, and showed the smallest MSE. To predict the performance degradation due to climate change, the climate change response variables were classified into three categories: climate exposure, sensitivity, and adaptive capacity. The performance degradation prediction was performed at each facility using the developed performance evaluation model and the climate change response variables.

• Journal of the Korean Data and Information Science Society
• /
• 제28권4호
• /
• pp.937-945
• /
• 2017

The purpose of using a control chart is to detect any change that occurs in the process. When control charts are used to monitor processes, we want to identify this changes as quickly as possible. Many problems in quality control involve a vector of observations of several characteristics rather than a single characteristic. Multivariate CUSUM or EWMA charts have been developed to address the problem of monitoring covariance matrix or the joint monitoring of mean vector and covariance matrix. However, control charts tend to work poorly when we use the highly correlatted variables. In order to overcome it, Hawkins (1991) proposed the use of regression adjustment variables. In this paper, to monitor covariance matrix, we investigate the performance of MEWMA-type control charts with and without the use of regression adjusted variables.

• Structural Engineering and Mechanics
• /
• 제60권3호
• /
• pp.413-431
• /
• 2016

A sensitivity analysis estimates the effect of the change in the uncertain variable parameter on the probability of the structural failure. A novel fuzzy random reliability sensitivity measure of the failure probability is proposed to consider the effect of the epistemic and aleatory uncertainties. The uncertainties of the engineering variables are modeled as fuzzy random variables. Fuzzy quantities are treated using the ${\lambda}$-cut approach. In fact, the fuzzy variables are transformed into the interval variables using the ${\lambda}$-cut approach. Genetic approach considers different possible combinations within the search domain (${\lambda}$-cut) and calculates the parameter sensitivities for each of the combinations.