• 한국농림기상학회지
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• 제23권2호
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• pp.134-140
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• 2021

농업용 유리온실 또는 플라스틱하우스의 투과율을 산정하거나 영농형 태양광 하부 작물의 수광량을 평가할 때, 그리고 작물 군락 광합성량을 모의하거나 분석할 때에 직달과 산란 일사량을 구분하여 접근할 필요가 있다. 본고에서는 산란과 직달 일사량 자료의 농업적 활용 촉진을 위해 나주에서 2019년 5월부터 2020년 11월까지 측정한 자료를 공개하였다. 또한, 기존 연구에서 9개의 산란계수 추정식을 본 자료로 검증하였다. 추정식들 대부분은 결정계수(R²)가 0.79~0.80, RMSE가 0.13~0.15의 범위를 가졌다. 직달·산란 일사량의 농업적 활용을 높이기 위해 본 데이터뿐만 아니라 다양한 자료가 관측되고 공개되어야 할 것이고, 그에 따른 추정식도 정교화될 필요가 있다.

• 대한방사선방어학회:학술대회논문집
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• 대한방사선방어학회 2011년도 춘계 학술발표회 및 심포지엄
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• pp.6-7
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• 2011

• 대기
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• 제25권1호
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• pp.149-154
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• 2015

As an attempt to improve fog predictability at Incheon International Airport (IIA) we couple the 3D weather forecasting model currently operational in Korea Meteorological Administration (regional Unified Model, UM_RE) with a 1D turbulence model (PAFOG). The coupling is done by extracting the meteorological data from the 3D model and properly inserting them in the PAFOG model as initial conditions and external forcing. The initial conditions include surface temperature, 2 m temperature and dew point temperature, geostrophic wind at 850 hPa and vertical profiles of temperature and dew point temperature. Moisture and temperature advections are included as external forcing and updated every hr. To validate the performance of the coupled system, simulation results of the coupled system are compared to those of the 3D model alone for the 22 sea fog cases observed over the Yellow Sea. Three statistical indices, i.e., Root Mean Square Error (RMSE), linear correlation coefficient (R) and Critical Success Index (CSI), are examined, and they all indicate that the coupled system performs better than the 3D model alone. These are certainly promising results but more improvement is required before the coupled system can actually be used as an operational fog forecasting model. For the RMSE, R, and CSI values for the coupled system are still not good enough for operational fog forecast.

• 한국측량학회지
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• 제38권2호
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• pp.97-107
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• 2020

To analyze temporal and spatial changes in vegetation, it is necessary to determine the associated continuous distribution and conduct growth observations using time series data. For this purpose, the normalized difference vegetation index, which is calculated from optical images, is employed. However, acquiring images under cloud cover and rainfall conditions is challenging; therefore, time series data may often be unavailable. To address this issue, La et al. (2015) developed a multilinear simulation method to generate missing images on the target date using the obtained images. This method was applied to a small simulation area, and it employed a simple analysis of variables with lower constraints on the simulation conditions (where the environmental characteristics at the moment of image capture are considered as the variables). In contrast, the present study employs variables that reflect the growth characteristics of vegetation in a greater simulation area, and the results are compared with those of the existing simulation method. By applying the accumulated temperature, the average coefficient of determination (R²) and RMSE (Root Mean-Squared Error) increased and decreased by 0.0850 and 0.0249, respectively. Moreover, when data were unavailable for the same season, R² and RMSE increased and decreased by 0.2421 and 0.1289, respectively.

• 한국농공학회논문집
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• 제46권5호
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• pp.107-116
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• 2004

A GIS-based paddy inundation simulation system which is capable of simulating temporal and spatial inundation processes was established and applied in this paper. The system is composed of HEC-GeoHMS, and HEC-GeoRAS modules which interface the GIS and flood runoff models, and HEC-HMS, and HEC-RAS models which estimate the flood runoff. It was used to simulate storm runoff and inundation for a small rural watershed, the Baran HP#7, which is 10.69 $km^2$ in size. The simulated peak runoff, time to peak, and total direct runoff for eight storms were compared with the observed data. The results showed that the coefficient of determination ($R^2$) for the observed peak runoff was 0.99 and an error, RMSE, 11.862 $m^3$/s for calibration stages. In the model verification, $R^2$ was 0.99 and RMSE 1.296 $m^3$/s. Paddy inundation for each paddy growing stages in study watershed were estimated using verified inundation simulation system when probability rainfall was applied.

• 한국환경과학회지
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• 제26권4호
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• pp.421-432
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• 2017

In this study, we examined the suitability of ten disinfection models for predicting the inactivation of Artemia sp. via single or combined physical and chemical treatments. The effect of Hydraulic Retention Time (HRT) on the inactivation of Artemia sp. was examined experimentally. Disinfection models were fitted to the experimental data by using the GInaFiT plug-in for Microsoft Excel. The inactivation model were evaluated on the basis of RMSE (Root Mean Square Error), SSE (mean Sum Square Error) and $r^2$. An inactivation model with the lowest RMSE, SSE and $r^2$ close to 1 was considered the best. The Weibull+Tail model was found to be the most appropriate for predicting the inactivation of Artemia sp. via electrolytic treatment and electrolytic-ultrasonic combined treatment. The Log-linear+Tail model was the most appropriate for modeling inactivation via homogenization and combined electrolytic-homogenization treatment. The double Weibull disinfection model was the most suitable for the predicting inactivation via ultrasonic treatment.

• 로봇학회논문지
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• 제12권2호
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• pp.206-216
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• 2017

This paper proposes a method to simultaneously estimate two degrees of freedom in wrist forces (extension - flexion, adduction - abduction) and one degree of freedom in grasping forces using Electromyography (EMG) signals of the forearms. To correlate the EMG signals with the forces, we applied a multi - layer perceptron(MLP), which is a machine learning method, and used the characteristics of the muscles constituting the forearm to generate learning data. Through the experiments, the similarity between the MLP target value and the estimated value was investigated by applying the coefficient of determination ($R^2$) and root mean square error (RMSE) to evaluate the performance of the proposed method. As a result, the $R^2$ values with respect to the wrist flexion-extension, adduction - abduction and grasping forces were 0.79, 0.73 and 0.78 and RMSE were 0.12, 0.17, 0.13 respectively.

• 한국농공학회지
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• 제45권6호
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• pp.119-127
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• 2003

This paper documents recent efforts to validate the GIS-based hydrologic models, HEC-HMS and HEC-GeoHMS by the US Army Corps of Engineers. HMS and Geo-HMS were used to simulate storm runoff from a small rural watershed, the Balan HS#6. The watershed is 3.85 $\textrm{km}^2$ in size. The watershed topographic, soils, and land use data were processed using the GIS tool fur the models. Input parameters were retrieved and calibrated with the field data. The simulated peak runoff, time to peak, and total direct runoff fer twenty three storms were compared with the observed data. The results showed that the coefficient of determination($R^2$) for the observed peak runoff was 0.95 and an error, RMSE, 3.08 $\textrm{m}^3$/s for calibration stages. In the model verifications, $R^2$ was 0.89 and RMSE 6.79 $\textrm{m}^3$/s, which were slightly less accurate than the calibrated data. The simulated flood hydrographs were well compared to the observed. It was concluded that HMS and GeoHMS are applicable to flood analyses for rural watersheds.

• Journal of Forest and Environmental Science
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• 제30권2호
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• pp.201-207
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• 2014

This study was conducted to estimate the best-fit nonlinear height-DBH growth models for Larix kaempferi in Gangwon and North Gyeongsang province in South Korea. Exponential, Modified Logistic, Chapman-Richards, and Weibull function were used for estimating height-DBH models. To evaluate the selected models, $R^2$, RMSE, MD, MAD, and residual plots were performed in each model. Also, the coefficients and patterns in models of the previous studies were compared with those in this study. The result showed that Weibull equation was found to be the best-fit model with $R^2$=0.9837, RMSE=2.6133, MD=0.0089, and MAD=2.0896. All model parameters in our study had similar values to those in the previous models except for asymptotic parameter a. Our research result showed that Gangwon and North Gyeongsang province were superior to other provinces with regard to height growth for Larix kaempferi.

• KIEAE Journal
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• 제11권1호
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• pp.15-20
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• 2011

Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design. For the six locations (Seoul, Incheon, Daejeon, Deagu, Gwangju and Busan) in South Korea where the global hourly solar irradiation (GHSI) is currently measured, GHSI was calculated using a comparatively simple cloud cover radiation model (CRM) and sunshine fraction radiation model (SFRM). The result was that the measured and calculated values of GHSI were similar for the six regions. Results of cloud cover and sunshine fraction models have been compared with the measured data using the coefficient of determination (R2), root-mean-square error (RMSE) and mean bias error (MBE). The strength of correlation R2 varied within similar ranges: 0.886-0.914 for CRM and 0.908-0.934 for SFRM. Average MBE for the CRM and SFRM were 6.67 and 14.02 W/m2, respectively, and average RMSE 104.36 and 92.15 W/m2. This showed that SFRM was slightly accurate and used many regions as compared to CRM for prediction of GHSI.