• 한국대기환경학회지
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• 제2권1호
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• pp.81-90
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• 1986

Hanna - Gifford Model and Air Quality Display Model(AQDM) were validated in the simulation of $SO_2$ and TSP concentrations of Seoul City. The observed data which were measured at 16 sites of air monitoring system conducted by Seoul metropolitan city in 1984 were compared with the simulated data and the results were obtained as follows; 1. Several different meteorological data were examined: The particularities of meteorological data was not an influencing factor in the validity of simulation. The simulations of $SO_2$ by Hanna - Gifford model and by AQDM showed close correlation coefficients between the observed data and the simulated data (r = 0.71 - 0.78). 2. The simulation models showed different validities with the seasonal variation: The correlation coefficients (r) between the observed and the simulated by Hanna - Gifford Model for $SO_2$ and TSP were 0.86 and 0.80 in Spring, 0.63 and 0.66 in Summer, 0.76 in Autumn and 0.81 and 0.93 in Winter respectively. Those by AQDM were 0.73 and 0.68 in Spring, 0.56 and 0.79 in Summer, 0.77 and 0.76 in Autumn and 0.64 and 0.68 in Winter respectively. 3. The simulated data by two models had a close relationships: The correlation coefficients between them were 0.96 for $SO_2$, and 0.93 for TSP. With the above results, the application of models was discussed; Hanna - Gifford model was less valid in the simulation for the air quality of $SO_2$ and TSP in Seoul in Summer and AQDM also was not valid for $SO_2$ in Summer and in Winter and for TSP in Spring.

• 성인간호학회지
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• 제18권2호
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• pp.213-222
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• 2006

Purpose: This study was designed to construct a structural model for explaining model health-related quality of life in acquired people with physical disabilities. Method: The hypothetical model of this study was consisted of 6 latent variables and 14 observed variables. Exogenous variables included in this model were physical status and economical level. Endogenous variables were social attitudes, family function, self-esteem, and health-related quality of life. Data were collected from 226 acquired people with physical disabilities residing in Seoul and Kyunggi-do from January to February, 2005. The collected data were analyzed using SAS 8.2 version and LISREL 8.32 version program. Results: The results of the fitness test of the modified model were follow as; ${\chi}^2=67.479$ (df=50, p=.05), GFI=.959, AGFI=.914, SRMR=.049, NFI=.961, NNFI=.979, CN=249.244. Health-related quality of life was influenced directly by physical status, economic level, and social attitudes and accounted for 88.8% of the variance by these factors. Conclusion: These results suggest that physical status is the most significant effect on health-related quality of life, and social attitudes and economic level are important factors having influences on health- related quality of life. Therefore improving physical status and economic level, and modifying negative attitudes are necessary to increase health-related quality of life of acquired people with acquired physical disabilities.

• 한국IT서비스학회지
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• 제11권1호
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• pp.211-221
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• 2012

Many metric-based classification models have been proposed to predict fault-proneness of software module. This paper presents two prediction models using Bayesian classifier which is one of the most popular modern classification algorithms. Bayesian model based on Bayesian probability theory can be a promising technique for software quality prediction. This is due to the ability to represent uncertainty using probabilities and the ability to partly incorporate expert's knowledge into training data. The two models, Na$\ddot{i}$veBayes(NB) and Bayesian Belief Network(BBN), are constructed and dimensionality reduction of training data and test data are performed before model evaluation. Prediction accuracy of the model is evaluated using two prediction error measures, Type I error and Type II error, and compared with well-known prediction models, backpropagation neural network model and support vector machine model. The results show that the prediction performance of BBN model is slightly better than that of NB. For the data set with ambiguity, although the BBN model's prediction accuracy is not as good as the compared models, it achieves better performance than the compared models for the data set without ambiguity.

• 품질경영학회지
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• 제24권1호
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• pp.137-145
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• 1996

We propose a model which is useful for the analysis of the spatial time series data. The proposed model utilized the linear dependences across the spatial units as well as over time. Three stage model fitting procedures are suggested and the real data is analyzed.

• Ecology and Resilient Infrastructure
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• 제9권1호
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• pp.24-35
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• 2022

수질분야에서 물재해 안정성 강화를 위해 과거와 현재의 수질을 분석하여 예측하는 기술을 지속적으로 고도화하는 것이 필요하며 데이터 기반의 예측 모형이 하나의 대안으로 대두되고 있다. 데이터 기반 모형은 복잡하고 광범위한 자료의 양을 기반으로 구축되기 때문에 보다 신뢰도 있는 결과를 얻을 수 있는 입력자료의 조합을 위한 상관관계 분석방법의 적용이 필수적이다. 본 연구에서는 보다 신속하고 정확한 데이터 기반의 수질 예측 모형을 구성하기 위한 선행단계로 Gamma Test를 적용하였다. 먼저 팔당댐의 다양한 수문조건에 따른 해당 유역의 복잡성과 정밀성이 재현된 과거와 현재의 일단위 수질을 최대한 확보하고자 물리적 기반 모형 (HSPF, EFDC)을 구동하였다. 팔당댐 수질예측지점과 팔당댐으로 유입되는 주요 하천의 수질을 대상으로 Gamma Test를 수행한 후 해석결과 (Gamma, Gradient, Standar Error, V-Ratio)를 통해 최적의 자료조합을 선정하는 방법을 제시하였다. 본 연구의 결과는 데이터 기반 모형 구축 시 반복적인 수행과정을 생략하여 시간을 단축하면서 보다 효율적으로 최적의 입력자료를 선정할 수 있는 정량적인 기준을 보여준다.

• 한국대기환경학회지
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• 제26권6호
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• pp.666-682
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• 2010

The forecasting system for Today's and Tomorrow's PM10 was developed based on the statistical model and the forecasting was performed at 9 AM to predict Today's 24 hour average PM10 concentration and at 5 PM to predict Tomorrow's 24 hour average PM10. The Today's forecasting model was operated based on measured air quality and meteorological data while Tomorrow's model was run by monitored data as well as the meteorological data calculated from the weather forecasting model such as MM5 (Mesoscale Meteorological Model version 5). The observed air quality data at ambient air quality monitoring stations as well as measured and forecasted meteorological data were reviewed to find the relationship with target PM10 concentrations by the regression analysis. The PM concentration, wind speed, precipitation rate, mixing height and dew-point deficit temperature were major variables to determine the level of PM10 and the wind direction at 500 hpa height was also a good indicator to identify the influence of long-range transport from other countries. The neural network, regression model, and decision tree method were used as the forecasting models to predict the class of a comprehensive air quality index and the final forecasting index was determined by the most frequent index among the three model's predicted indexes. The accuracy, false alarm rate, and probability of detection in Tomorrow's model were 72.4%, 0.0%, and 42.9% while those in Today's model were 80.8%, 12.5%, and 77.8%, respectively. The statistical model had the limitation to predict the rapid changing PM10 concentration by long-range transport from the outside of Korea and in this case the chemical transport model would be an alternative method.

• 한국측량학회지
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• 제19권3호
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• pp.253-261
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• 2001

현재 하천의 수질관리를 위하여 여러 수질모델이 개발되어 있으며, 이러한 수질예측모델에 각종 수질관리에 따른 대안을 적용시킴으로써 그 효과를 사전에 모의 평가하고 있다. 그러나 이러한 수질모델을 적용하기 위해서는 복잡한 형식의 입력자료 구축단계가 요구되고 있으며 모델을 통한 타당한 분석결과를 산출하였음에도 불구하고 모델 자체의 표현의 한계성으로 인하여 효과적인 의사결정 자료로서의 활용이 미약한 실정이다. 본 연구는 GSIS를 이용한 하천수질모의에 관한 연구로서, 기존 수질모델의 이러한 제약을 극복하고자 GSIS환경에서 유역별 오염부하량을 산정하고 입력자료를 생성하며 모의결과를 시각화하는 인터페이스를 개발함에 있어 모델의 전ㆍ후처리과정에 GSIS를 적용하는 유연한 통합(Flexible coupling) 방법을 이용하여 수질모델과 GSIS를 통합하였다. 수질모델로는 기존의 하천수질모델 중 우리나라의 실정에 적합하여 비교적 정확하고 또한 그 적용이 간단하여 많은 지역에서 실제 적용되어 그 적용성이 검증된 QUAL2E 모델을 사용하였다.

• 한국컴퓨터정보학회논문지
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• 제27권12호
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• pp.189-195
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• 2022

정부는 공공데이터의 민간 개방, 활용을 장려함으로써 신산업, 일자리 창출 등 창조경제 활성화에 기여하는 것을 주요 국정과제로 삼고 있다. 그리고 고품질 공공데이터 보유를 위해 공공데이터 품질관리 수준평가 진행 등의 활동을 통해 공공데이터 품질 향상을 도모하고 있다. 그러나 품질진단 도구 사용자의 데이터 전문성, 이해도에 따라 공공데이터 품질관리 수준평가 결과에 격차가 발생하기 때문에 진단 결과의 정확성을 보장하기 어렵다. 본 논문은 데이터 이해도가 낮은 사용자의 진단 결과에 대한 정확성을 보장하기 위해 데이터 품질진단 기준 중 유효성 진단에 적용 가능한 공공데이터 품질관리 수준평가 도메인규칙 매핑 모델을 제안하였다. 또한 모델에 실제 데이터를 적용한 결과 공공데이터 품질진단의 안정성과 정확성을 높이는 것을 확인하였다.

• 한국환경과학회지
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• 제9권6호
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• pp.455-462
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• 2000

This study aims at the development of the model for a forecasting of water quality in river basins using artificial neural network technique. Water quality by Artificial Neural Network Model forecasted and compared with observed values at the Sangju q and Dalsung stations in Nakdong river basin. For it, a multi-layer neural network was constructed to forecast river water quality. The neural network learns continuous-valued input and output data. Input data was selected as BOD, CO discharge and precipitation. As a result, it showed that method III of three methods was suitable more han other methods by statistical test(ME, MSE, Bias and VER). Therefore, it showed that Artificial Neural Network Model was suitable for forecasting river water quality.

• Journal of Information Technology Applications and Management
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• 제23권3호
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• pp.71-86
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• 2016

This paper proposes a new software quality model composed of a hierarchy of software quality views and three software quality characteristics models. The software view hierarchy is composed of two levels : end view and means view at the first level, contingency view and intrinsic view as sub-views of means view. Three software quality characteristics models are activity quality characteristics model, contingency quality characteristics model, and intrinsic quality characteristics model, which correspond to end view, contingency view, and intrinsic view respectively. This paper also reclassifies characteristics of ISO/IEC 25000 series SQuaRE's software product quality model according to the proposed software quality model. The results illustrate clearly the shortcomings of SQuaRE's product quality model and how to overcome them. First of all, most of SQuaRE's product characteristics should be redefined and conceptually clarified according to the views on which they are really rested. Much more characteristics should be supplemented too. After that, rigorous empirical researches will become relevant. Causal relationships between activity quality characteristics and characteristics of means view should be empirically researched.