• 환경영향평가
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• 제29권4호
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• pp.272-285
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• 2020

본 연구에서는 3차원 기상 및 대기질 모델의 입출력 자료를 평가하는 데 필요한 통계 검증지표를 선별하고, 선정된 검증지표의 기준치를 조사하여 그 결과를 요약하였다. 여러 국내외 문헌과 최근 논문 검토를 통해 최종 선정된 통계 검증지표는 MB (Mean Bias), ME (Mean Error), MNB (Mean Normalized Bias Error), MNE (Mean Absolute Gross Error), RMSE (Root Mean Square Error), IOA (Index of Agreement), R (Correlation Coefficient), FE (Fractional Error), FB (Fractional Bias)로 총 9가지이며, 국내외 문헌을 통해 그 기준치를 확인하였다. 그 결과, 기상모델의 경우 대부분 MB와 ME가 주요 지표로 사용되어 왔고, 대기질 모델 결과는 NMB와 NME 지표가 주로 사용되었으며, 그 기준치의 차이를 분석하였다. 아울러 이들 통계 검증지표값을 이용하여 모델 예측 결과를 효과적으로 비교하기 위한 표출 도식으로 축구 도식, 테일러 도식, Q-Q (Quantile-Quantile) 도식의 장단점을 분석하였다. 나아가 본 연구 결과를 기반으로 우리나라의 산악지역의 특수성 등이 잘 고려된 통계 검증지표의 기준치 설정 등의 추가연구가 효과적으로 진행될 수 있기를 기대한다.

• 한국대기환경학회지
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• 제33권1호
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• pp.11-18
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• 2017

The performance of a modeling system consisting of WRF model v3.3 and CMAQ model v4.7.1 for forecasting $PM_{2.5}$ concentrations were evaluated during the period May 2012 through December 2014. Twenty-four hour averages of $PM_{2.5}$ and its major components obtained through filter sampling at the Bulgwang intensive measurement station were used for comparison. The mean predicted $PM_{2.5}$ concentration over the entire period was 68% of the mean measured value. Predicted concentrations for major components were underestimated except for $NO_3{^-}$. The model performance for $PM_{2.5}$ generally tended to degrade with increasing the concentration level. However, the mean fractional bias (MFB) for high concentration above the $80^{th}$ percentile fell within the criteria, the level of accuracy acceptable for standard model applications. Among three bias correction methods, the ratio adjustment was generally most effective in improving the performance. Albeit for limited test conditions, this analysis demonstrated that the effects of bias correction were larger when using the data with a larger bias of predicted values from measurement values.

• Macromolecular Research
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• 제15권6호
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• pp.491-497
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• 2007

NPT Monte Carlo simulations were performed to calculate the molecular properties of syndiotactic poly(vinyl chloride) (PVC) and syndiotactic poly(vinyl alcohol) (PVA) melts using the configurational bias Monte Carlo move, concerted rotation, reptation, and volume fluctuation. The density, mean square backbone end-to-end distance, mean square radius of gyration, fractional free-volume distribution, distribution of torsional angles, small molecule solubility constant, and radial distribution function of PVC at 0.1 MPa and above the glass transition temperature were calculated/measured, and those of PVA were calculated. The calculated results were compared with the corresponding experimental data and discussed. The calculated densities of PVC and PVA were smaller than the experimental values, probably due to the very low molecular weight of the model polymer used in the simulation. The fractional free-volume distribution and radial distribution function for PVC and PVA were nearly independent of temperature.

• Environmental Engineering Research
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• 제24권4호
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• pp.572-581
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• 2019

The emission of hydrogen sulfide (H₂S) from the Kahrizak landfill was studied. Firstly, the field measurements were conducted in the summer and winter seasons; and the samples were analyzed using Jacob method. We predicted the H₂S concentrations in the downwind using AERMOD and ISCST3. According to the AERMOD, the maximum concentration of H₂S in the summer and winter were 117 ㎍/㎥ and 205 ㎍/㎥ respectively. The downwind concentrations reached zero at the distance of 35 km from the leachate treatment plant. The Geometric mean bias, Geometric variance, Fractional bias, Fraction of predictions within a factor of two of the observations and Normalized mean square error for the AERMOD were 0.58, 1.35, -0.12, 1.91 and 0.042, respectively in the summer and 1.39, 1.35, -0.05, 1.46 and 0.027 in the winter; and for the ISCST3, were 0.85, 1.03, 0.02, 1.45 and 0.04 in the summer and 1.18, 1.03, 0.15, 1.16 and 0.04 in the winter. The results of the AERMOD were compared with the ISCST3 and indicated that the AERMOD performance was more suitable than the ISCST3.

• 응용통계연구
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• 제15권2호
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• pp.395-403
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• 2002

반응표면방법론에서의 세번째 단계에서는 일차모형이 가정되고, 반응표면의 곡선효과는 중앙점과 2수준 부분실시법에서의 실험을 통해서 검토된다. 참모형이 2차 모형인 경우를 가정하자. 최적실험계획을 선택하기 위해서 Box와 Draper(1959)는 관심영역에서 예측치 y(x)의 평균제곱오차를 적분한 값인 가중평균제곱오차(AMSE)를 최소화 시키는 최적실험계획 기준을 제안하였다. AMSE는 예측치의 가중분산과 가중제곱편의 량의 합으로 분할될 수 있다. AMSE는 실험계획 적률과 참모형의 회귀계수들의 값에 종속되어서 가중평균제곱오차를 최 소화하는 실험 계획을 찾기는 불가능하다. 실용적인 대안으로 Box와 Draper(1959)는 가중제곱편의 량을 최소화하는 실험계획을 제안했고, 이 실험계획의 상자점들이 중앙점을 향해서 축소됨을 보였다. 이 논문에서는 표준화된 회귀계수들의 값에 대해서 실험계획의 최소효율을 최대화하는 강건한 실험계획을 제안한다.

• 한국환경과학회지
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• 제12권7호
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• pp.809-816
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• 2003

The short-term version of Industrial Source Complex Model(ISCST3) was evaluated for estimating short-term concentrations using criteria pollutant(SO$_2$, NO$_2$, CO, PM10) data from emission inventory of Young Tong area in Suwon for the year 2002. The contribution of pollutant concentration from point, line, area sources was found 21.8, 76.5 and 1.6%. Statistical parameters, such as correlation coefficient, index of agreement(IA), normalized mean square error(NMSE) and fractional bias(FB) were calculated for each pollutants. The model performance were found good for PM10(82%) and NO$_2$(69%), but poor for SO$_2$(34%) and CO(13%).

• Asian-Australasian Journal of Animal Sciences
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• 제25권9호
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• pp.1237-1247
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• 2012

The objective of this study was to evaluate the predictions of dry matter intake (DMI) and average daily gain (ADG) of Vietnamese Yellow (Vang) purebred and crossbred (Vang with Red Sindhi or Brahman) bulls fed under Vietnamese conditions using two levels of solution (1 and 2) of the large ruminant nutrition system (LRNS) model. Animal information and feed chemical characterization were obtained from five studies. The initial mean body weight (BW) of the animals was 186, with standard deviation ${\pm}33.2$ kg. Animals were fed ad libitum commonly available feedstuffs, including cassava powder, corn grain, Napier grass, rice straw and bran, and minerals and vitamins, for 50 to 80 d. Adequacy of the predictions was assessed with the Model Evaluation System using the root of mean square error of prediction (RMSEP), accuracy (Cb), coefficient of determination ($r^2$), and mean bias (MB). When all treatment means were used, both levels of solution predicted DMI similarly with low precision ($r^2$ of 0.389 and 0.45 for level 1 and 2, respectively) and medium accuracy (Cb of 0.827 and 0.859, respectively). The LRNS clearly over-predicted the intake of one study. When this study was removed from the comparison, the precision and accuracy considerably increased for the level 1 solution. Metabolisable protein was limiting ADG for more than 68% of the treatment averages. Both levels differed regarding precision and accuracy. While level 1 solution had the least MB compared with level 2 (0.058 and 0.159 kg/d, respectively), the precision was greater for level 2 than level 1 (0.89 and 0.70, respectively). The accuracy (Cb) was similar between level 1 and level 2 (p = 0.8997; 0.977 and 0.871, respectively). The RMSEP indicated that both levels were on average under-or over-predicted by about 190 g/d, suggesting that even though the accuracy (Cb) was greater for level 1 compared to level 2, both levels are likely to wrongly predict ADG by the same amount. Our analyses indicated that the level 1 solution can predict DMI reasonably well for this type of animal, but it was not entirely clear if animals consumed at their voluntary intake and/or if the roughness of the diet decreased DMI. A deficit of ruminally-undegradable protein and/or a lack of microbial protein may have limited the performance of these animals. Based on these evaluations, the LRNS level 1 solution may be an alternative to predict animal performance when, under specific circumstances, the fractional degradation rates of the carbohydrate and protein fractions are not known.