• ETRI Journal
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• 제34권5호
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• pp.696-705
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• 2012

Accurate synthesis models based on artificial neural networks (ANNs) are proposed to directly obtain the physical dimensions of an asymmetric coplanar waveguide with conductor backing and substrate overlaying (ACPWCBSO). First, the ACPWCBSO is analyzed with the conformal mapping technique (CMT) to obtain the training data. Then, a modified genetic-algorithm-Levenberg-Marquardt (GA-LM) algorithm is adopted to train ANNs. In the algorithm, the maximal relative error (MRE) is used as the fitness function of the chromosomes to guarantee that the MRE is small, while the mean square error is used as the error function in LM training to ensure that the average relative error is small. The MRE of ANNs trained with the modified GA-LM algorithm is less than 8.1%, which is smaller than those trained with the existing GA-LM algorithm and the LM algorithm (greater than 15%). Lastly, the ANN synthesis models are validated by the CMT analysis, electromagnetic simulation, and measurements.

• 한국컴퓨터정보학회논문지
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• 제27권4호
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• pp.27-36
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• 2022

본 논문에서는 이러한 어류 가공 현장의 문제점을 개선하기 위해서 AI 머신 비전을 이용한 어류의 목표 중량 절단 예측기법을 제안한다. 제안하는 방법은 먼저 입력된 물고기의 평면도와 정면도를 촬영하여 이미지기반의 전처리를 수행한다. 그런 다음 RANSAC(RANdom SAMmple Consensus)를 사용하여 어류의 윤곽선을 추출한 다음 3D 모델링을 사용하여 물고기의 3D 외부 정보를 추출한다. 이어서 추출된 3차원 특징 정보와 측정된 중량 정보를 머신러닝하여 목표 중량에 대한 절단 지점을 예측하기 위한 신경망 모델을 생성한다. 마지막으로 제안기법을 통해 예측된 절단 지점으로 직접 절단한 뒤 그 중량을 측정하였다. 그리고 측정된 무게를 목표 무게와 비교하여 MAE(Mean Absolute Error) 와 MRE(Mean Relative Error)와 같은 평가 방법을 사용해 성능을 평가하였다. 그 결과, 목표 중량과 비교해 3% 이내의 평균 오차율을 달성하였다. 제안된 기법은 향후 자동화 시스템과 연계되어 수산업 발전에 크게 기여할 것으로 전망한다.

• Nuclear Engineering and Technology
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• 제55권4호
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• pp.1400-1409
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• 2023

In this study, three condensation models of the CUPID code, i.e., the resolved boundary layer approach (RBLA), heat and mass transfer analogy (HMTA) model, and an empirical correlation, were tested and validated against the COPAIN and CAU tests. An improvement on HMTA model was also made to use well-known heat transfer correlations and to take geometrical effect into consideration. The RBLA was a best option for simulating the COPAIN test, having mean relative error (MRE) about 0.072, followed by the modified HMTA model (MRE about 0.18). On the other hand, benchmark against CAU test (under natural convection and occurred on a slender tube) indicated that the modified HMTA model had better accuracy (MRE about 0.149) than the RBLA (MRE about 0.314). The HMTA model with wall function and the empirical correlation underestimated significantly, having MRE about 0.787 and 0.55 respectively. When using the HMTA model, consideration of geometrical effect such as tube curvature was essential; ignoring such effect leads to significant underestimation. The HMTA and the empirical correlation required significantly less computational resources than the RBLA model. Considering that the HMTA model was reasonable accurate, it may be preferable for large-scale simulations of containment.

• 한국경영과학회지
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• 제23권1호
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• pp.67-95
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• 1998

This research addresses flow time prediction in the dynamic unbalanced job shop scheduling environment. The specific purpose of the research is to develop the job flow time prediction model in the dynamic unbalance djob shop. Such factors as job characteristics, job shop status, characteristics of the shop workload, shop dispatching rules, shop structure, etc, are considered in the prediction model. The regression prediction approach is analyzed within a dynamic, make-to-order job shop simulation model. Mean Absolute Lateness (MAL) and Mean Relative Error (MRE) are used to compare and evaluate alternative regression models devloped in this research.

• 농업과학연구
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• 제49권4호
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• pp.771-783
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• 2022

In this study, the feasibility of alternative tractor Roll Over Protective Structure (ROPS) designed to evaluate conditions required for testing was confirmed. In accordance with Organization for Economic Cooperation and Development (OECD) code 4, the required load energy of the tractor ROPS was determined. First, the tractor ROPS test was performed and a repeated test was performed using a simplified ROPS as an alternative tractor ROPS. The test procedure is first rearward, second lateral, and last forward based on ROPS. The load test device consists of a load cell that measures force and a LVDT that measures deformation. Precision was confirmed by calculating the relative standard deviation of the simplified ROPS repeated test. Accuracy was analyzed by calculating the mean relative error between the mean measured values in the simplified ROPS test and the tractor ROPS test. As a result, the relative standard deviation was less than 2.5% for force and 3.3% for maximum deformation overall, showed the highest precision in lateral load. The mean relative error value for force measured at the lateral load of simplified ROPS was 0.5%, showing the highest accuracy. In the front load test, the mean relative error of maximum deformation was 20.5%, showing the lowest accuracy. The mean relative error (MRE) was high in the forward load test was because of structural factors of the ROPS. The simplified ROPS model is expected to save money and time spent preparing tractors.

• 농업과학연구
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• 제47권2호
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• pp.315-326
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• 2020

In this study, a real-time crop recognition system was developed for an unmanned farm machine for upland farming. The crop recognition system was developed based on a stereo camera, and an image processing framework was proposed that consists of disparity matching, localization of crop area, and estimation of crop height with coordinate transformations. The performance was evaluated by attaching the crop recognition system to a tractor for five representative crops (cabbage, potato, sesame, radish, and soybean). The test condition was set at 3 levels of distances to the crop (100, 150, and 200 cm) and 5 levels of camera height (42, 44, 46, 48, and 50 cm). The mean relative error (MRE) was used to compare the height between the measured and estimated results. As a result, the MRE of Chinese cabbage was the lowest at 1.70%, and the MRE of soybean was the highest at 4.97%. It is considered that the MRE of the crop which has more similar distribution lower. the results showed that all crop height was estimated with less than 5% MRE. The developed crop recognition system can be applied to various agricultural machinery which enhances the accuracy of crop detection and its performance in various illumination conditions.

• 한국대기환경학회지
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• 제15권6호
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• pp.779-789
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• 1999

To support daily ground-level $O_3$ forecasting in Seoul, a transfer function model(TFM) has been developed by using surface meteorological data and pollutant data(previous-day [$O_3$] and [$NO_2$]) from 1 May to 31 August in 1997. The forecast performance of the TFM was evaluated by statistical comparison with $O_3$ concentration observed during September it is shown that correlation coefficient(R), root mean squared error(RMSE), normalized mean squared error(NMSE) and mean relative error(MRE) were 0.73, 15.64, 0.006 and 0.101, respectively. The TFM appeared to have some difficulty forecasting very high $O_3$ concentrations. To compare with this model, multiple regression model(MRM) was developed for the same period. According to statistical comparison between the TFM and MRM. two models had similar predictive capability but TFM based on $O_3$ concentration higher than 60 ppb provided more accurate forecast than MRM. It was concluded that statistical model based on TFM can be useful for improving the accuracy of local $O_3$ forecast.

• 한국지구과학회지
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• 제36권1호
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• pp.109-124
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• 2015

레이더 반사도를 이용한 강수추정의 개선을 위해 새로운 접근 방식인 경북대학교에서 개발한 하이브리드 고도면을 이용한 강수량 추정기법(Hybrid Surface Rainfall, KNU-HSR)을 사용하였다. KNU-HSR기법은 지형에코와 레이더 빔차폐의 영향을 받지 않는 2차원 하이브리드 고도면에서의 반사도를 이용하여 강수량을 추정한다. 본 연구에서는 정적 HSR 및 동적 HSR기법이 사용되었으며 비교 검증되었다. 정적 HSR은 빔차폐지도와 지형에코지도를 사용하며, 동적 HSR은 정적 HSR에 추가적으로 실시간 퍼지로직 품질관리를 통한 품질지수지도를 사용한다. 검증을 위해 상관계수(correlation coefficient), 총비율(total ratio), 평균편의(mean bias), 정규화된 표준편차(normalized standard deviation), 평균 상대오차(mean relative error)를 사용하였으며, 10개 강우사례의 지상우량계 강우자료를 이용하여 두 HSR의 강우추정 성능을 평가하였다. 모든 검증지수에서 동적 HSR은 반사도 보정을 하지 않은 정적 HSR에 비해 더 우수한 성능을 보였다. 동적 HSR은 레이더로부터 근거리에서는 과대추정하였으며 원거리에서는 빔 폭 확장 및 빔 고도증가로 인해 과소추정하였다. 동적 HSR의 정규화된 표준편차와 평균상대오차는 레이더로부터의 거리에 관계없이 가장 좋은 결과를 보였다. 정적 HSR은 약한 강우강도에서 상당히 과대추정하였으나 동적 HSR은 모든 강우강도에서 1.0에 총비율을 보였다. 반사도의 시스템오차 보정 후, 동적 HSR의 정규화된 표준편차와 평균상대오차는 각각 약 20%와 15%로 개선되었다.

• 한국물환경학회지
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• 제35권6호
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• pp.589-597
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• 2019

The purpose of this study was improve accuracy the IOPs inversion model(IOPs-IM) developed in 2016 for phycocyanin(PC) concentration estimation in the Nakdong River. Additionally, two optimum models were developed and evaluated with 2017 measurement field spectral data for the Geum River and the Yeongsan River. The used measurement data for IOPs-IM analyzation was randomly classified as training and verification materials at the ratio of 2:1 in all data sets. Using the training data set from 2015-2017, accuracy results of the IOPs-IM generally improved for the Nakdong River. The RMSE(Root Mean Square Error) decreased by 14 % compared to 2016. For the GeumRiver, the results of the IOPs-IM were suitable, except for some point results in 2016. Results of the IOPs-IM in the Yeongsan River followed the overall 1:1 line and MAE(Mean Absolute Error) was lower than other rivers. But the RMSE and MAE values were higher. As a result of applying the validation data to the IOPs-IM, the accuracy of the Nakdong River was reduced to RMSE 17.7 % and MRE 16.4 %, respectively compared with 2016. However, the MRE(Mean Relative Error) was estimated to be higher by 400 % in the Geum River, and the RMSE was more than 100 mg/㎥ of the Yeongsan River. Therefore, it is necessary to get the continuously data with various sections of each river for obtain objective and reliable results and the models should be improved.

• Computers and Concrete
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• 제19권4호
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• pp.435-442
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• 2017

In recent years, the use of supplementary cementing materials, especially in addition to concrete, has been the subject of many researches. Rice husk ash (RHA) is one of these materials that in this research, is added to the roller compacted concrete as one of the pozzolanic materials. This paper evaluates how different contents of RHA added to the roller compacted concrete pavement specimens, can influence on the strength and permeability. The results are compared to the control samples and determined optimal level of RHA replacement. As it was expected, RHA as supplementary cementitious materials, improved mechanical properties of roller compacted concrete pavement (RCCP). Also, the application of adaptive neuro-fuzzy inference system (ANFIS) in predicting the permeability and compressive strength is investigated. The obtained results shows that the predicted value by this model is in good agreement with the experimental, which shows the proposed ANFIS model is a useful, reliable, fast and cheap tool to predict the permeability and compressive strength. A mean relative error percentage (MRE %) less than 1.1% is obtained for the proposed ANFIS model. Also, the test results and performed modeling show that the optimal value for obtaining the maximum compressive strength and minimum permeability is offered by substituting 9% and 18% of the cement by RHA, respectively.