• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.354-354
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• 2021

2020년은 장마기간이 49일간 지속됨에 따라 침수, 산사태 등 많은 홍수피해가 발생하였다. 특히 서울에서는 한강 본류의 수위가 급격하게 증가함에 따라 둔치 및 도로 침수 피해가 발생하였다. 이처럼 하천의 수위증가로 인한 홍수피해에 대응하기 위해 홍수통제소 및 기초지자체에서는 홍수특보를 발령한다. 이 홍수특보는 수위관측소 지점별 계획홍수량의 50 %, 70 % 이상의 홍수량이 발생할 경우 홍수주의보와 홍수경보가 발령되며, 이 기준은 각 권역별로 동일하다. 하지만 2017년 의정부시에서는 중랑천 수위증가로 인해 주변 지역에 침수피해가 발생하였지만, 이때 홍수량은 계획홍수량 대비 약 30 %에 불과하였다. 이처럼 한강권역 내 하천수위 증가로 인한 홍수피해는 계획홍수량의 50 % 이내에서 발생하기도 한다. 이에 본 연구에서는 한강권역을 대상으로 현재 2단계로 발령되는 홍수특보를 3단계로 세분화하고자 하였다. 단계별 홍수량 위험기준을 산정하기 위해 과거 홍수피해 발생 이력이 있는 한강권역 내 43개의 수위관측소 지점을 선정하였으며, 지점별 홍수기 동안의 홍수량 및 피해액 자료를 수집하였다. 각 단계별 홍수량 기준을 산정하기 위해서는 로지스틱 회귀분석 방법을 활용하여 피해발생 확률을 산정하였다. 1단계 기준은 계획홍수량 대비 홍수량 비율과 홍수피해 발생여부를 고려한 이항 로지스틱 회귀분석 모델을 구축한 후 3계 도함수에 적용하여 홍수피해 발생확률이 급격하게 증가하는 특이점을 산정하였다. 2단계와 3단계 기준은 다항 로지스틱 회귀분석 중 계층형 로지스틱 회귀분석을 활용하여 지점별 피해액 비율이 60 ~ 80 %, 80 ~ 100 % 구간에 속할 확률을 산정하고, 1단계와 동일한 방법으로 특이점을 산정하였다. 그 결과 지점별로 기존 제공되고 있는 홍수특보 기준을 과거 발생한 홍수피해를 고려하여 세분화할 수 있었으며, 이 결과는 지역별 홍수피해 저감대책에 활용될 수 있을 것으로 판단된다.

• Journal of Ocean Engineering and Technology
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• v.26 no.2
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• pp.39-47
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• 2012

The objective of this study was to develop a strength prediction model using a polynomial regression analysis based on the experimental results obtained from ninety samples. As the results of a correlation analysis between various mixing factors and unconfined compressive strength using SPSS (statistical package for the social sciences), the governing factors in the strength of lightweight soil were found to be the crumb rubber content, bottom ash content,and water-cement ratio. After selecting the governing factors affecting the strength through the correlation analysis, a strength prediction model, which consisted of the selected governing factors, was developed using the polynomial regression analysis. The strengths calculated from the proposed model were similar to those resulting from laboratory tests (R2=87.5%). Therefore, the proposed model can be used to predict the strength of lightweight mixtures with various mixing ratios without time-consuming experimental tests.

• Solar Energy
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• v.20 no.1
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• pp.21-29
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• 2000

In this research, the intensity of solar energy, which was injected to the different angle plane every hour day by day, was technically documented and quantitatively analyzed through actual observations. In order to group every days into days with similar intensity, graph was drawn with respect to time for every day and each area value under the curve was calculated. Then, the search for grouped days having similar intensity curve patterns was carried out. In order to maximize the efficiency of solar energy systems, the optimum incident angle of absorber plate was derived.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.105-117
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• 2022

This study analyzes the effects between stock returns and interest rate spread, difference between long-term and short-term interest rate through the polynomial linear regression analysis. The existing research concentrated on the business forecast through the interest rate spread focusing on the US market. The previous studies verified the interest rate spread based on the leading indicators of business forecast by moderating the period of long-term/short-term interest rates and analyzing the degree of leading. After the 7th reform of composite indices of business indicators in Korea of 2006, the interest rate spread was included in the items of composing the business leading indicators, which is utilized till today. Nevertheless, there are a few research on stock returns of each industry and interest rate spread in domestic stock market. Therefore, this study analyzed the stock returns of each industry and interest rate spread targeting Korean stock market. This study selected the long-term/short-term interest rates with high causality through the regression analysis, and then understood the correlations with each leading period and industry. To overcome the limitation of the simple linear regression analysis, polynomial linear regression analysis is used, which raised explanatory power. As a result, the high causality was verified when using differences between returns of corporate bond(AA-) without guarantee for three years by leading six months and call rate returns as interest rate spread. In addition, analyzing the stock returns of each industry, the relation between the relevant interest rate spread and returns of the automobile industry was the closest. This study is significant in the aspect of verifying the causality of interest rate spread, business forecast, and stock returns in Korea. Even though it could be limited to forecast the stock price by using only the interest rate spread, it would be working as a strong factor when it is properly utilized with other various factors.

• Journal of Korea Technology Innovation Society
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• v.19 no.4
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• pp.687-710
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• 2016

This study aims to empirically estimate distributed lag effects of expenditure by type of R&D on scientific publication in the national R&D program. To analyze the lag structure between them, we used a dataset comprised of panel data from 104 technologies categorized by 6T (IT, BT, NT, ST, ET, CT) from 2007 to 2014, and employed multiple regression analysis based on the polynomial distributed lag model. This is because it is highly likely to emerge multicollinearity, if a distributed lag model without special restrictions is applied to multiple regression analysis. The main results are as follows. In the case of basic research, its lag effects are relatively evenly distributed during four years. On the other hand, the applied research and experimental development have distributed lag effects for three years and two years respectively. Therefore, when it comes to analyzing performance of scientific publication, it is necessary to be performed with characteristics of the time lag by type of R&D.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.411-424
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• 2011

The studies of congruence in organizational research have explored the concepts such as person-job fit person-organization fit, or person-environment fit. The relevant studies dealt with the fit level as an important influencing factor on the performance. In particular, researchers have agreed that employees can be motivated by the high level fit of person-organization. However, few research developing an alternative methodological approach has been done. For the purpose mentioned above the statistics like D, |D| or $D^2$ and the Q values such as Q(the correlation between two sets of interval measures) or $Q_r$(the correlation between two rankings) have been conventionally adopted in spite of numerous methodological problems. In general, these traditional indices such as difference scores, or Q values, are nondirectional and add an extra weight to differences of lager magnitude. Therefore, Edwards (1993) introduced the polynomial regression and the response surface analysis to overcome flaws with conventional approaches. However, the method-ological approaches did not reflect the profile characteristics of person-organizational value fit and wouldn't be a proper solution for the fit level of person-organization value maximizing performance. Hence, this paper investigates alternative methodological approaches, the multivariate polynomial regression and the multiple response surface analysis, to avoid the problems issued from conventional ways.

• Journal of Korea Water Resources Association
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• v.40 no.7
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• pp.511-521
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• 2007

The objective of this study is to develop a method of rainfall adjustment on duration and topographic elevation for rainfall data in Jejudo. The method of rainfall adjustment is based on the polynomial regression analysis for the hourly rainfall data and the distribution of observatories of korea meteorological administration. As the results of modeling have shown, duration and rainfall are more correlated than topographic elevation and rainfall, and the model which considers only an elevation exaggerates the amount of rainfall adjustment. Hence the model of duration-elevation-rainfall is more competitive to the natural rainfall event than the model of topographic elevation-rainfall. However this model require to supplement a small number of rainfall observatories and short observed period.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.257-266
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• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.857-870
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• 2010

This study was conducted to investigate the relationship between the socio-demographic factors and the Korean consumers palatability evaluation grades with Hanwoo sensory evaluation data from 2006 to 2008 by National Institute of Animal Science. The dichotomy logistic regression model and the multinomial logistic regression model are fitted with the independent variables such as the consumer living location, age, gender occupation, monthly income, beef cut and the the palatability grade as the categorical dependent variable and tenderness, 리avor and juiciness as the continuous dependent variable. Stepwise variable selection procedure is incorporated to find the final model and odds ratios are calculated to nd the associations between categories.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.9-19
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• 2024

As using public monitoring data, analysing a trends of water quality change, establishing a criteria to determine abnormal status and constructing a regression model that can predict Chlorophyll-a, an indicator of eutrophication, was studied. Accordingly, the three freshwater lakes were selected, approximately 20 years of water quality monitoring data were analyzed for periodic changes in water quality each year using regression analysis, and a method for determining abnormalities was presented by the standard deviation at confidence level 95%. By calculating the temporal change rate of Chlorophyll-a from irregular observed data, analyzing correlations between the rate and other water quality items, and constructing regression models, a method to predict changes in Chlorophyll-a was presented. The results of this study are expected to contribute to freshwater lake water quality management as an approximate water quality prediction method using the statistical model.