• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5B
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• pp.405-414
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• 2011

The adaptive network-based fuzzy inference system (ANFIS) which had a success for time series prediction and system control was applied for modeling the hourly runoff in the Gapcheon watershed. The ANFIS used the antecedent rainfall and runoff as the input. The ANFIS was trained by varying the various simulation factors such as mean areal rainfall estimation, the number of input variables, the type of membership function and the number of membership function. The root mean square error (RMSE), mean peak runoff error (PE), and mean peak time error (TE) were used for validating the ANFIS simulation. The ANFIS predicted runoff was in good agreement with the measured runoff and the applicability of ANFIS for modelling the hourly runoff appeared to be good. The forecasting ability of ANFIS up to the maximum 8 lead hour was investigated by applying the different input structure to ANFIS model. The accuracy of ANFIS for predicting the hourly runoff was reduced as the forecasting lead hours increased. The long-term predictability of ANFIS for forecasting the hourly runoff at longer lead hours appeared to be limited. The ANFIS might be useful for modeling the hourly runoff and has an advantage over the physically based models because the model construction of ANFIS based on only input and output data is relatively simple.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.135-147
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• 2017

We, for the first time, estimated daily and monthly surface nitrogen dioxide ($NO_2$) volume mixing ratio (VMR) using three regression models with $NO_2$ tropospheric vertical column density (OMIT-rop $NO_2$ VCD) data obtained from Ozone Monitoring Instrument (OMI) in Seoul in South Korea at OMI overpass time (13:45 local time). First linear regression model (M1) is a linear regression equation between OMI-Trop $NO_2$ VCD and in situ $NO_2$ VMR, whereas second linear regression model (M2) incorporates boundary layer height (BLH), temperature, and pressure obtained from Atmospheric Infrared Sounder (AIRS) and OMI-Trop $NO_2$ VCD. Last models (M3M & M3D) are a multiple linear regression equations which include OMI-Trop $NO_2$ VCD, BLH and various meteorological data. In this study, we determined three types of regression models for the training period between 2009 and 2011, and the performance of those regression models was evaluated via comparison with the surface $NO_2$ VMR data obtained from in situ measurements (in situ $NO_2$ VMR) in 2012. The monthly mean surface $NO_2$ VMRs estimated by M3M showed good agreements with those of in situ measurements(avg. R = 0.77). In terms of the daily (13:45LT) $NO_2$ estimation, the highest correlations were found between the daily surface $NO_2$ VMRs estimated by M3D and in-situ $NO_2$ VMRs (avg. R = 0.55). The estimated surface $NO_2$ VMRs by three modelstend to be underestimated. We also discussed the performance of these empirical modelsfor surface $NO_2$ VMR estimation with respect to otherstatistical data such asroot mean square error (RMSE), mean bias, mean absolute error (MAE), and percent difference. This present study shows a possibility of estimating surface $NO_2$ VMR using the satellite measurement.

• ETRI Journal
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• v.26 no.3
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• pp.218-228
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• 2004

Using stereo images with ephemeris data from the Korea Multi-Purpose Satellite-1 electro-optical camera (KOMPSAT-1 EOC), we performed geometric modeling for three-dimensional (3-D) positioning and evaluated its accuracy. In the geometric modeling procedures, we used ephemeris data included in the image header file to calculate the orbital parameters, sensor attitudes, and satellite position. An inconsistency between the time information of the ephemeris data and that of the center of the image frame was found, which caused a significant offset in satellite position. This time inconsistency was successfully adjusted. We modeled the actual satellite positions of the left and right images using only two ground control points and then achieved 3-D positioning using the KOMPSAT-1 EOC stereo images. The results show that the positioning accuracy was about 12-17 m root mean square error (RMSE) when 6.6 m resolution EOC stereo images were used along with the ephemeris data and only two ground control points (GCPs). If more accurate ephemeris data are provided in the near future, then a more accurate 3-D positioning will also be realized using only the EOC stereo images with ephemeris data and without the need for any GCPs.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.4
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• pp.9-19
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• 2014

The objective of this study was to evaluate of the Tank model in simulating runoff discharge from rural watershed in comparison to the SWAT (Soil and Water Assessment Tool) model. The model parameters of SWAT was calibrated by the shuffled complex evolution-university Arizona (SCE-UA) method while Tank model was calibrated by genetic algorithm (GA) and validated. Four dam watersheds were selected as the study areas. Hydrological data of the Water Management Information System (WAMIS) and geological data were used as an input data for the model simulation. Runoff data were used for the model calibration and validation. The determination coefficient ($R^2$), root mean square error (RMSE), Nash-Sutcliffe efficiency index (NSE) were used to evaluate the model performances. The result indicated that both SWAT model and Tank model simulated runoff reasonably during calibration and validation period. For annual runoff, the Tank model tended to overestimate, especially for small runoff (< 0.2 mm) whereas SWAT model underestimate runoff as compared to observed data. The statistics indicated that the Tank model simulated runoff more accurately than the SWAT model. Therefore the Tank model could be a good tool for runoff simulation considering its ease of use.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.63.1-63.1
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• 2015

In this study, we determine coronal electron density distributions by analyzing DH type II radio observations based on the assumption: a DH type II radio burst is generated by the shock formed at a CME leading edge. For this, we consider 11 Wind/WAVES DH type II radio bursts (from 2000 to 2003 and from 2010 to 2012) associated with SOHO/LASCO limb CMEs using the following criteria: (1) the fundamental and second harmonic emission lanes are well identified; (2) its associated CME is clearly identified in the LASCO-C2 or C3 field of view at the time of type II observation. For these events, we determine the lowest frequencies of their fundamental emission lanes and the heights of their leading edges. Coronal electron density distributions are obtained by minimizing the root mean square error between the observed heights of CME leading edges and the heights of DH type II radio bursts from assumed electron density distributions. We find that the estimated coronal electron density distribution ranges from 2.5 to 10.2-fold Saito's coronal electron density models.

• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.66-72
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• 2014

This paper introduces an asynchronous multiple radar fusion algorithm for space object tracking. To estimate orbital motion of space object, a multiple radar scenario which jointly measures single object with different sampling time indices is described. STK/ODTK is utilized to determine realization of orbital motion and joint coverage of multiple radars. Then, asynchronous fusion algorithm is adapted to enhance the estimation performance of orbital motion during which multiple radars measure the same time instances. Monte-Carlo simulation results demonstrate that the proposed asynchronous multi-sensor fusion scheme better than single linearized Kalman filter in an aspect of root mean square error.

• Journal of Astronomy and Space Sciences
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• v.28 no.4
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• pp.291-298
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• 2011

The atmospheric infrared sounder (AIRS) sensor loaded on the Aqua satellite observes the global vertical structure of atmosphere and enables verification of the water vapor distribution over the entire area of South Korea. In this study, we performed a comparative analysis of the accuracy of the total precipitable water (TPW) provided as the AIRS level 2 standard retrieval product by Jet Propulsion Laboratory (JPL) over the South Korean area using the global positioning system (GPS) TPW data. The analysis TPW for the period of one year in 2008 showed that the accuracy of the data produced by the combination of the Advanced Microwave Sounding Unit sensor with the AIRS sensor to correct the effect of clouds (AIRS-X) was higher than that of the AIRS IR-only data (AIRS-I). The annual means of the root mean square error with reference to the GPS data were 5.2 kg/$m^2$ and 4.3 kg/$m^2$ for AIRS-I and AIRS-X, respectively. The accuracy of AIRS-X was higher in summer than in winter while measurement values of AIRS-I and AIRS-X were lower than those of GPS TPW to some extent.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.907-923
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• 2020

For the severe haze situation in the Beijing-Tianjin-Hebei region, conventional fine particulate matter (PM2.5) concentration prediction methods based on pollutant data face problems such as incomplete data, which may lead to poor prediction performance. Therefore, this paper proposes a method of predicting the PM2.5 concentration based on image analysis technology that combines image data, which can reflect the original weather conditions, with currently popular machine learning methods. First, based on local parameter estimation, autoregressive (AR) model analysis and local estimation of the increase in image blur, we extract features from the weather images using an approach inspired by free energy and a no-reference robust metric model. Next, we compare the coefficient energy and contrast difference of each pixel in the AR model and then use the percentages to calculate the image sharpness to derive the overall mass fraction. Furthermore, the results are compared. The relationship between residual value and PM2.5 concentration is fitted by generalized Gauss distribution (GGD) model. Finally, nonlinear mapping is performed via the wavelet neural network (WNN) method to obtain the PM2.5 concentration. Experimental results obtained on real data show that the proposed method offers an improved prediction accuracy and lower root mean square error (RMSE).

• Atmosphere
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• v.25 no.1
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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.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.56.4-57
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• 2015

We present the optical design and a sensitivity analysis for a wide field of view (FOV) instrument operating at UV and IR wavelengths. The ongoing investigation is performed in collaboration with Omnisys Instruments (Sweden) and focuses on a telluric-limb-viewing instrument that will fly in a low Earth orbit to study mesospheric wave structures over a wide range of horizontal scales in the altitude range 80 - 100 km. The instrument has six wavelength channels which consist of 4 channels of IR and 2 of UV. We are proposing an optical design based on three mirror aplanatic off-axis reflective system. The entrance pupil diameter and effective focal length are 45 mm and 270 mm, respectively. The FOV is $5.5^{\circ}{\times}1^{\circ}$ and the secondary mirror is set for stop. The optical specification is required to have an encircled energy of at least 80 % within a diameter of 21 um. We performed sensitivity analysis for the longest wavelength of 772 nm in consideration of the diffraction limit of system. The results show that tolerance limits for positions and angles of the mirrors are not very sensitive compared with typical error budgets of manufacturing and assembling process. The secondary mirror has the most sensitive tolerance for surface figure of 250 nm in root-mean-square.