PDSI와 범지구적 해수면온도와의 저빈도 상관성 분석

오태석,김성실,문영일 한국방재학회 2010 한국방재학회논문집 Vol.10 No.3

가뭄은 인간이 극복하기 힘든 자연재해로서 가뭄지역의 경제를 어렵게 할 뿐 아니라 생태계까지 파괴하기 때문에 전 세계적으로 가장 두려워하는 관심 재해 중 하나이다. 따라서 본 연구에서는 대표적인 가뭄지수인 팔머가뭄지수와 범지구적 해수면 온도의 상관관계를 분석하였다. 먼저 팔머가뭄지수를 산정하여 과거 가뭄발생연도와 비교분석을 실시하였다. 비교분석을 결과 대부분의 과거 가뭄사상과 지수가 일치하는 것으로 분석되었다. 상관성 분석을 위해 팔머가뭄지수 산정을 위한 지수인 강수자료와 온도자료를 월평균강수량과 월평균온도 자료로 산정하여 군집분석을 실시하였다. 우리나라 기상청관할에 있는 61개 지점을 선정하여 월평균강우량과 월평균온도 자료로 군집분석결과 총 6개의 군집을 형성하는 것으로 분석되었다. 또한, 군집분석결과와 팔머가뭄지수의 주성분 분석을 실시하였다. 주성분 분석을 통해 전체 자료의 분산을 80% 이상 설명할 수 있는 14개의 시계열자료를 추출하였다. 추출된 팔머가뭄지수의 주요 성분과 범지구적 해수면 온도와의 상관성 분석결과 팔머가뭄지수는 양의 상관관계가 음의 상관관계보다 큰 것으로 분석되었으며, 태평양에서 관측되는 해수면 온도와 통계적으로 유의한 상관관계를 갖는 해수면 온도 구역을 확인할 수 있었다. 이를 통해 해수면 온도를 이용하여 우리나라에 발생할 수 있는 가뭄의 예측 가능성을 제시하였다 Drought is one of disaster causing factors to produce severe damage in the World because drought is destroyed to the ecosystem as well as to make difficult the economy of the drought area. This study, using Palmer Drought Severity Index carries out correlation analysis with sea surface temperatures. Comparative analysis carries out by calculated Palmer Drought Severity Index and past drought occurrence year. Result of comparative analysis, PDSI indexes were in accord with the past drought. Cluster analysis for correlation analysis carries out using precipitation and temperature that is input datas palmer drought severity index, and the result of cluster analysis was classified as 6. Also, principal component carries out using result of cluster analysis. 14 principal component analyze out through principal component analysis. Using analyzed 14 principal component carries out correlation analysis with sea surface temperature that is delay time from 0month until 11month. Correlation analysis carries out sea surface temperatures and calculated cycle component of the low frequency through Wavelet Transform analysis form principal component. Result of correlation analysis, yang(+) correlation is bigger than yin(-) correlation. It is possible to check similar correlation statistically the area of sea surface temperature with sea surface temperature in the Pacific. Forecasting possibility of the future drought make propose using sea surface temperature.

Efficient Correlation Method for Satellite Thermal Analysis Model Using Multiple Linear Regression and Optimization Algorithms

Jaewon Kang,김건웅,Somin Shin,김정호 한국항공우주학회 2023 International Journal of Aeronautical and Space Sc Vol.24 No.5

As the thermal analysis model of satellites is used as an important indicator for thermal design, it must accurately simulate the thermal behaviour of actual satellites for precise thermal design. To increase the accuracy of the thermal analysis model, it must be correlated using the thermal balance test data for actual satellite models. To achieve this, we herein propose an efficient correlation method for satellite thermal analysis models using multiple linear regression techniques with quadratic terms and optimization algorithms. The proposed method reduces the amount of computation by choosing dominant parameters through sensitivity analysis and creating a multiple linear regression model that can replace the thermal analysis model in the subsequent optimization process. Subsequently, optimization algorithms are applied to the multiple linear regression model to perform the correlation of the thermal analysis model. In this study, the numerical validation of the proposed method was performed using numerical data from a reference thermal analysis model to verify the reliability and accuracy of the proposed method before it was applied to the correlation of the thermal analysis model using experimental data. The thermal analysis result of the reference thermal analysis model was set as the target value to correlate, and quantitative performance evaluation was performed for various combinations of optimization algorithms and design of experiments methods by comparing the estimated analysis parameters. The results of this study demonstrate that the proposed method can efficiently produce an accurate correlation model for thermal analysis.

요인 개수 결정을 위한 평행분석의 정확성 평가

임상돈,장승민 한국심리학회 2017 한국심리학회지 일반 Vol.36 No.4

Parallel analysis is a method of estimating the number of factors by comparing the eigenvalues ​​of sample data with the eigenvalues ​​of random data. This method is considered to be theoretically more valid and empirically more accurate in estimating the number of factors than other methods, such as Kaiser method and scree test, that estimate the number of factors based on the eigenvalues. However, several criticisms have been raised about the validity of the rationale for parallel analysis and various modifications have been proposed. There have also been concerns about the conditions under which parallel analysis shows relatively low accuracy. The current study examined the rationale and limitations of the use of eigenvalues ​​and parallel analysis to estimate the number of factors, and based on this, we specified the conditions under which the accuracy of parallel analysis may be low. We also examined, through a simulation, the effects of various factors that may affect the accuracy of parallel analysis and confirmed the conditions where cautions are needed when applying parallel analysis. The results of the simulation show that the accuracy of estimating the number of factors in the parallel analysis is greatly influenced by the size of factor correlations, the magnitude of factor loadings, the number of factors, and the number of variables per factor. In addition, we confirmed that the accuracy of the parallel analysis is significantly lower when a factor model includes a weak factor with low factor loadings. Overall, the accuracy of the parallel analysis for the reduced correlation matrix (PA-PAF) was higher than the parallel analysis for the correlation matrix (PA-PCA), which in particular, PA-PAF showed high accuracy when factor correlations were high, and PA-PCA showed high accuracy when factor correlations were low. Based on the results of the simulation analyses, we proposed sample sizes required for parallel analysis to provide accuracy of 90% or higher under conditions with different levels of factor correlation, factor loading, and the number of factors. 평행분석은 표본 자료의 고윳값과 무선 자료의 고윳값을 비교하여 요인의 개수를 추정하는 방법이다. 이 방법은 고윳값에 근거하여 요인의 개수를 추정하는 다른 절차들(카이저 방법, 스크리 검사)보다 이론적으로 더 타당한 근거를 갖고 있고 경험적으로도 요인의 개수를 더 정확히 추정하는 것으로 평가 받는다. 그러나 평행분석의 이론적 근거의 타당성에 대해서도 여러 비판이 제기되어 왔고 이에 따른 다양한 수정 절차들도 제안되었다. 또한 평행분석이 상대적으로 낮은 정확성을 나타내는 조건들에 대한 우려도 있어 왔다. 본 연구는 고윳값과 평행분석이 요인의 개수를 추정하는 데 사용될 수 있는 이론적 근거와 한계를 검토하고 이를 바탕으로 평행분석의 정확성이 낮게 나타날 수 있는 조건들을 구체화하였다. 또한 모의실험을 통해 평행분석의 정확성에 영향을 줄 수 있는 다양한 요인들의 효과를 검토하고 평행분석의 사용에 주의를 요하는 조건들을 확인하였다. 모의실험의 결과는 평행분석의 요인수 추정 정확률이 요인상관의 크기, 요인부하량의 크기, 요인의 개수, 요인당 변수의 개수에 따라 크게 영향을 받으며 정확률이 낮은 조건에서 표본크기의 영향이 매우 크다는 것을 보였다. 또한 요인부하량이 낮은 변수들로 구성된 약한 요인이 포함된 경우 요인수 추정의 정확률이 크게 낮아짐을 확인하였다. 전반적으로 상관행렬에 대한 평행분석(PA-PCA)보다 축소상관행렬에 대한 평행분석(PA-PAF)의 정확률이 높았으며 특히 요인상관이 높은 경우에는 PA-PAF가, 요인상관이 낮은 경우에는 PA-PCA가 높은 정확률을 보이는 경향이 확인되었다. 마지막으로 모의실험의 결과를 기초로 요인상관의 크기, 요인부하량의 크기, 요인의 개수의 조합으로 구성되는 다양한 조건에서 평행분석이 90% 이상의 정확률을 제공하기 위해 요구되는 표본크기를 제안하였다.

시공간을 고려한 환경생태적 우수지역과 환경성질환의 상관성 분석 연구 : 환경·국토계획 통합 계획에서의 활용방안을 중심으로

김근한 ( Geunhan Kim ),강선아,윤정호,최희선,송영명 한국환경연구원 2019 수시연구보고서 Vol.2019 No.-

국토의 환경성을 종합적으로 평가한 국토환경성평가지도의 환경생태적 평가 등급과 건강간의 관계를 분석하였다. 본 연구는 국토환경성지도의 환경생태적 평가가 1등급 지역인 환경생태적 우수 지역을 대상으로 심혈관 질환, 뇌혈관 질환, 인후두염, 환경성 질환 중 일부 대표 질환들을 선정하여 국토환경성 우수지역과 건강과의 관계를 살펴보았다. 특히 국토환경성 우수지역의 경우 사람들이 거주하고 활동하는 시가지로부터 거리별 환경생태적 우수지역이 건강에 미치는 영향을 분석하기 위해 시가지로부터 300m, 500m, 1km, 3km, 5km 내의 환경생태적 우수지역을 추출하여 상관분석 하였다. 이러한 상관분석에는 Quasi-Poisson Regression을 활용하였고, 오염변인(confounding variables)으로 시군구의 평균소득수준, 전국 측정망으로부터 획득한 평균 대기오염물질의 농도 값을 전국단위로 보간법을 적용하여 전국단위의 대기오염물질 농도를 확보하고, 시군구별 평균 대기오염물질 농도를 계산하여 평가에 반영하였다. 분석은 전국의 시군구 단위로 각 질환별 진료건수를 활용하였으며, 이때 시군구별 인구로 나누어 원단위로 통일시킨 후 분석에 활용하였다. 환경생태적 평가 결과 또한 각 시군구별 면적으로 나누어 면적 비율로 원단위 변환 후 분석에 활용하였다. 분석 결과는 다음과 같다. 우선 실험에 활용하고자 선정된 21개 질환 중 상관분석을 수행하여 환경생태적 우수지역의 면적 비율과 질환별 치료건수 비율과의 상관성 분석 결과 호흡기결핵, COPD, 폐렴, 고혈압, 뇌졸중, 심근경색, 협심증, 허혈성심질환, 비염, 아토피피부염, 천식과 같이 11개 질환에 음의 상관관계가 나타났으며, 해당 질환 중 고혈압, COPD, 폐렴, 심근경색, 허혈성심질환, 천식은 사람들이 거주 및 생활하는 시가지로부터 300m, 500m, 1km, 3km, 5km와 같이 일정거리 내의 환경생태적 평가 1등급 면적 비율과 음의 상관관계가 나타남을 확인하였다. 이러한 분석 결과 11개 질환의 경우 환경생태적으로 우수한 지역의 면적비율이 높을수록 질환별 치료건수의 비율이 낮게 나타났으며, 이중 6개 질환은 거리까지 고려하였을 때 거주 또는 활동하는 시가화지역으로부터 가까운 거리에 환경생태적 우수지역이 많이 분포할수록 질환별 치료건수의 비율이 낮게 나타났는데, 이는 더 강한 음의상관관계를 보여준 것이다. 추가적으로 이렇게 도출된 6개 질환에 대해 어떠한 평가 항목이 중요 인자인지를 파악하기 위해 의사결정트리와 랜덤포레스트를 수행한 결과 시군구의 주거지역, 상업지역, 공업지역의 면적 또한 건강과의 연관성이 높게 나타났으며, 시군구의 대기질 또한 건강과의 연관성이 높게 나타났다. 특히 NO₂, O₃, CO, PM10 등은 높은 연관성이 높게 나타났으며, 추가적인 상관관계 분석을 통해 대기오염물질의 농도 또한 환경생태적 평가 결과와 밀접한 연관성이 나타남을 확인할 수 있었다. 이러한 국민의 건강과 국토의 환경성과의 상관성 관련 분석결과를 기반으로 국토-환경계획 통합관리에서의 활용을 검토할 수 있으며, 특히 제5차 국가환경종합계획, 제5차 국가종합계획 등 다양한 계획에서 활용 가능할 것으로 판단된다. 특히 도시기본계획 및 도시관리계획 등 도시지역의 보전과 개발을 고려한 공간계획을 수립해야 하는 계획단계에서 시가화지역 인근에 분포한 환경생태적 우수지역을 보호해야 하며, 이러한 사람들이 거주하고 생활하는 지역 중 환경생태적 우수지역이 근처에 없는 도시지역들은 향후 도시재생 등 다양한 방법을 이용하여 녹지공간을 확보하고 이러한 녹지공간이 환경생태적 우수지역으로 변화할 수 있도록 관리해야 할 것으로 판단된다. This study analyzed the relationship between the environmental and ecological assessment grade of the Environmental Conservation Value Assessment Map (ECVAM), which comprehensively assess the environmental impact of the national land, and health. It selected representative diseases among cardiovascular disease, cerebrovascular disease, pharyngitis, and environmental diseases in the areas with environmental and ecological grade 1 by the ECVAM and analyzed the relationship between the environmentally excellent region and the health. It extracted the environmentally and ecologically outstanding areas within 300 m, 500 m 1 km, 3 km, and 5 km from the downtown and analyzed the correlation to examine the effect of the environmentally and ecologically outstanding areas by distance from the downtown, where people live and work, on the health. The correlation analysis used the Quasi-Poisson regression with the average income level of municipalities and the municipality-level average atmospheric pollutant concentrations calculated from the national-level atmospheric pollutant concentrations, which interpolated the average atmospheric pollutant concentration obtained from the national measurement network to the national level, as the confounding variables. The analysis used the number of treatments for each disease in the municipality level divided by the population of the municipality to unify the basic unit. The environmental and ecological analysis results were also divided by the area of each municipality to convert it to the area ratio as the basic unit. The analysis results are described as follows: The correlation of 21 diseases selected for the analysis of the correlation between the area ratio of the environmentally and ecologically outstanding region and the treatment ratio of each disease. The analysis results showed that eleven diseases, such as respiratory tuberculosis, COPD, pneumonia, hypertension, stroke, myocardial infarction, angina pectoris, ischemic heart disease, rhinitis, atopic dermatitis, and asthma were negatively correlated. Of these diseases, hypertension, COPD, pneumonia, myocardial infarction, ischemic heart disease, and asthma were negatively correlated with the area ratio of environmental and ecological grade 1 within a certain distance, such as 300 m, 500 m, 1 km, 3 km, and 5 km from the downtown. Such analysis results indicated that the treatment ratio of each of 11 diseases was low as the area ratio of the environmentally and ecologically outstanding region as high. Moreover, regarding the distance from the downtown, the treatment ratio of the six diseases was lower when environmentally and ecologically outstanding regions were larger within the shorter distance from the downtown, and the negative correlation was stronger in that case. Additionally, we conducted the decision-making tree and random forest regression to identify the evaluation factors of the additionally extracted six diseases. The results showed that residential region, commercial region, and industrial region in the municipalities were also correlated to the health, and the atmospheric quality of the municipality was also highly correlated to the health. NO2, O3, CO, and PM10, in particular, showed a high correlation, and the additional correlation analysis confirmed that the atmospheric pollutant concentration was also closely related to the environmental and ecological evaluation results. The analysis results of the relationship between the people’s health and the environmental factors of the land can be utilized by the integrated land-environmental management plan, such as the Fifth National Environmental Master Plan and the Fifth National Master Plan. The spatial plans, such as basic urban plan and urban management plan that consider both conservation and development of urban areas, must include measures to protect the environmentally and ecologically outstanding regions near the downtown area. Urban areas that do not have nearby environmentally and ecologically outstanding regions should secure green spaces using various methods such as urban regeneration and manage them to transform them into excellent environmental and ecological excellent regions in the future.

A Teaching Quality Guarantee Model of Talents Training in Colleges and Universities Based on Grey Correlation Analysis

Wang Yan 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.6

There are many things to consider in teaching activities of colleges and universities. Teaching quality guarantee involves complex system engineering. In order to address multi-attribute evaluation of teaching quality, this paper proposes a teaching quality guarantee model of talents training based on grey correlation analysis. A new type of teaching quality guarantee system of talent training is constructed and factor sets for guarantee analysis are confirmed. Then, the state sets of the teaching quality guarantee analysis and classical domains are discussed. A teaching quality guarantee model of talents training is established based on grey correlation analysis in order to obtain the grey correlation coefficient and the grey correlation degree. The teaching quality level of talent training is judged according to the grey correlation degree. Finally, a case is studied to verify the model.

맥솔(脈率)과 심박변이도(心搏變移度)의 상관성(相關性) 연구(硏究)

양동훈 ( Dong-hoon Yang ),박영배 ( Young-bae Park ) 대한한의진단학회 2006 大韓韓醫診斷學會誌 Vol.10 No.2

Background: Pulse-respiration ratio has been used for estimating subject`s status in oriental medicine. Pulse and respiration is strongly associated with autonomic nerve system. But there is no research about correlation between pulse-respiration ratio and autonomic nerve system. Objectives: We performed this study to know correlation between pulse-respiration ratio and HRV(heart rate variability) that shows autonomic nerve system status well and to clarify clinical meaning of pulse-respiration ratio. Methods: After subject`s 10 minutes rest, we measured subject`s ECG, respiration pattern and HRV. In this research, subject`s number is 95(Male 50/Female 45). We calculated pulse-respiration ratio from ECG and respiration pattern. Then, we analyzed correlation between pulse-respiration ratio and HRV parameters in all subjects, 2 group divided by Wan-Maek(P-R ratio 4.28). We tried to compare HRV parameters among Wan-Maek, Sak-Maek and Ji-Maek group. Correlation analysis between pulse-respiration Ratio and pulse rate, respiration rate is performed. Finally correlation analysis between Respiration and HRV parameters in all subjects, 2 group divided by Wan-Maek(4.28) is studied. Results: 1. Mean pulse-respiration is 4.10±0.67, Mean pulse rate is 68.06±7.82bpm, Mean respiration rate is 16.81±2.72 times per minute in all subjects. 2. Correlation analysis between pulse-respiration ratio and HRV parameters of high pulse-respiration ratio group is not Significant. But, in low pulse-respiration ratio group, HFnorm(correlation coefficient 0.306, p= 0.018), InHF (0.308, p=0.002) is sig-nificantly correlated with pulse-respiration ratio. 3. Comparison of HRV parameters among Wan-Maek, Sak-Maek and Ji-Maek Group is not significant. 4. Pulse-respiration ratio is more affected by respiration rate(correlation coefficient -0.717, p= 0.000) than pulse rate (correlation coefficient 0.396, p=0.000). 5. Correlation analysis between respiration rate and HRV parameters of high pulse-respiration ratio group is not significant. But, in low pulse-respiration ratio group, HFnorm (correlation coefficient -0.327, p=0.011), LF/HF(0.346, p=0.007), 1nHF (-0.355, p=0.006) are significantly correlated with respiration rate. Conclusions: Pulse-respiration ratio and parasympathetic index has positive correlation. The closer Wan-maek, The higher parasympathetic index in low pulse-respiration ratio group. Respiration rate is more related with pulse-respiration ratio than pulse rate. Respiration is negatively correlated with autonomic parameters. And the slower respiration, the higher parasympathetic index in low pulse-respiration ratio group.

Correlation Between Tractor Variables and Loan Support Limit in South Korea Through Regression Analysis

황석준,김정훈,장문경,남주석 한국농업기계학회 2022 바이오시스템공학 Vol.47 No.3

Purpose The correlation between the major variables of tractors and the loan support limit was investigated through regression analysis. Methods The loan support limit according to engine power,weight, engine displacement, width, length, and height was surveyed for 118 tractors commercially available in South Korea. Simple linear regression analysis was performed to understand the effects of the individual variables on the loan support limit. Furthermore, the major variables with a high correlation with the loan support limit were selected through Pearson correlation analysis, and multiple linear regression analysis was performed. Results Simple regression models and multiple regression models were derived to predict the tractor loan support limit. The coefficient of determination and the root mean square error were calculated to determine the accuracy of each regression model. In the simple linear regression analysis, the coefficient of determination of the engine-power-based regression model was the highest (0.87), followed by weight, engine displacement, width, length, and height. Similarly, the root mean square error was the smallest in the engine-power-based regression model at 3,770,370 KRW. As a result of performing multiple linear regression analysis using engine power and weight, which exhibited a correlation coefficient of 0.8 or higher in Pearson correlation analysis, the coefficient of determination and the root mean square error were 0.88 and 3,699,940 KRW, respectively. Conclusion As the multiple regression model with engine power and weight as variables has a high coefficient of determination and small root mean square error, it is considered the most suitable for predicting the tractor loan support limit. The developed prediction model can save time and greatly help the decision-making process of farmers for purchasing agricultural tractors.

상관분석 및 의사결정나무를 통한 사출 성형품 변형의 영향 인자 분석

이용선,이은녕,황순환,한성렬 한국기계기술학회 2022 한국기계기술학회지 Vol.24 No.1

This paper analyzed the correlation between injection molding factors through correlation analysis. In addition, the decision-tree model, which is a white box model with excellent explanatory power, was used to obtain optimal molding conditions that satisfy multiple constraint conditions. First, 243 data to be used in the experiment were created through a full factorial design. Second, a correlation analysis was conducted to understand the correlation. Third, to verify the decision-tree model, the prediction performance was evaluated using RMSE. As a result, good prediction performance was confirmed. A decision-tree experiment analysis was conducted. As a result of the progress, the same results as the correlation analysis were derived. Based on the previous analysis results, optimal molding conditions were applied to CAE. As a result, the amount of deformation in the multi-cavity could be improved by about 1.1% and 2.72% while satisfying the constraint.

도로환경요인과 교통사고의 상관분석 및 사고추정모형 개발 (청주시 4지 신호교차로를 중심으로)

박정순·,김태영,유두선 대한교통학회 2007 대한교통학회지 Vol.25 No.2

The purpose of this study is to develop a traffic characteristic analysis, a correlation analysis with the variables of traffic characteristics, and accident estimation models while recognizing the seriousness of the traffic accidents. The analyses deal with the 181 4-legged signalized intersections that accounted for 1,183 out of 3,115 accidents in Cheongju in 2004. After measuring ADT, intersection area, average lane width, elevation, and other items as independent variables and the number of traffic accidents, the traffic accident rate (accidents per million entering vehicles), and equivalent property damage only (EPDO) figures as dependent variables which are estimated as influencing signalized intersection accidents, the estimation models are developed using correlation analysis and multiple regression analysis.In the analysis of the number of traffic accidents, the model indicates an R2 of 0.612, and five independent variables are taken as significant factors. In the analysis of traffic accident rates, the model indicates an R2 of 0.304 and five significant factors, including intersection area and ADT. Also, for the analysis of the EPDO numbers, which coincides with understanding the seriousness of the traffic accidents and the traffic characteristic analysis, the model indicates an R2 of 0.559, and four independent variables (ADT, main street average lane width, elevation, and speed limit) as significant factors. 본 연구의 목적은 신호교차로의 교통사고 심각성을 인식하고, 교통사고의 특성분석과 관련변수와의 상관분석 및 사고추정모형을 개발하는 것이다. 이러한 목적하에 본 연구에서는 2004년도 청주시 총 교통사고건수 3,115건 중 1,183건이 발생한 4지 신호교차로 전체(181개소)를 대상으로 하였다. 신호교차로 사고에 영향을 줄 것으로 판단되는 ADT, 교차로 면적, 평균차로폭 및 종단경사 등 독립변수들과 교통사고건수, 교통사고율(MEV) 및 EPDO를 종속변수로 선정하여, 상관분석 및 다중회귀분석을 통해 추정모형을 개발하였다. 모형개발 결과, 교통사고건수의 경우 ADT 등 5개의 변수가 주요 요인으로 분석되었으며(R2=0.612), 교통사고율(MEV)의 경우 교차로면적 등 5개 변수가 주요 요인으로 분석되었다(R2=0.304). 또한, 신호교차로 교통사고의 심각성 및 특성분석이라는 본 연구의 목적에 가장 부합되는 EPDO의 경우는 ADT, 주도로 평균차로폭, 상향종단경사, 제한속도 차 등 4개 변수가 주요 요인으로 분석되었다(R2=0.559)

변동차수 탈경향 방법을 통한 기상데이터의 상관성분석

차호환,김재화 한국물리학회 2014 새물리 Vol.64 No.10

We analyze the correlation of meteorological data with a periodic trend by using the recently proposed correlation-analysis methods. In order to make the time series stationary, we apply the varying polynomial-order detrending method to the nonstationary time series. By using this method, we obtained stable scaling exponents different from those obtained by using the ordinary detrending method, which showed a cross over around the periodic time point. We chose three locations on the Korean peninsula and found the autocorrelation and the cross-correlation exponents between the temperature and the relative humidity. From the obtained scaling exponents, we conclude that there are universal properties in the correlation, the so-called long-range memories in autocorrelations and cross-correlations. In addition to these scaling exponents associated with the correlations, we found that the cross-correlation coefficients, which quantify the level of cross-correlation, are somewhat different in each area. 최근에 제안된 상관분석법을 이용하여 전형적인 주기적 비정상 (nonstationary) 특성을 가지는 기상데이터의 상관성을 분석하여 보았다. 주기적 비정상 시계열을 정상 (stationary)화 하는 과정에서 변동차수\_탈경향분석 (varing polynomial order detrended analysis)방법을 사용함으로써 시계열의 주기성 때문에 일반적인 탈경향분석 (detrending analysis)방법에서 보이는 크로스오버가 사라져 안정적인 상관스케일 지수를 얻을 수 있음을 알았다. 우리는 한반도내의 세 지역을 선정하여 위의 방법을 사용함으로써 각 지역 내 기온과 상대습도 변동에 장기 기억성이라는 보편적 성질이 있음을 알았으며, 각 지역에서 온도-상대습도 기상데이터 사이의 변동차수 탈경향 교차상관분석 (DCCA-l(n))방법을 통하여 지역간에 비슷한 크기의 스케일지수를 갖는 교차상관성이 나타남을 확인하였다. 또한 장기교차상관성 여부를 보여주는 스케일지수와는 별도로 온도와 상대습도간의 상관강도를 수치화한 교차상관계수는 지역에 따라 조금씩 다른 값을 보이는 것을 알았다.