• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.42 no.3
• /
• pp.13-18
• /
• 2005

This paper presents a design of a multi-objective $H_2/H_{\infty}$ controller of an inverted pendulum with polytopic model by the stabilizing regulator and tracking performances. Multi-objective controllers are designed for polytopic models by the LMI design technique with convex algorithms. It is observed that the inverted pendulum controlled by any controller designed for each polytopic model is stably restored to the vertical angle position for initial values of larger tilt angles.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.5 no.1
• /
• pp.11-18
• /
• 2002

Directional breaking waves are generated by the component wave focusing both in direction and frequency based on constant wave steepness and constant wave amplitude spectrum models. The generated breaking waves are classified in the incipient, single and multi breaking waves. The characteristics of directional breaking waves are investigated in terms of surface profile parameters of wave crest steepness and asymmetry. The evolution of breaking wave characteristics is analyzed in a view of focusing efficiency. It shows that the front steepness and vertical asymmetry play an important role in breaking process, while the crest rear steepness and horizontal asymmetry are nearly constant during the process. The superposition of directional components greatly enhances the focusing efficiency and it suggests that characteristics of directional breaking waves may significantly different from uni-directional ones.

• Journal of the Korean earth science society
• /
• v.28 no.2
• /
• pp.214-226
• /
• 2007

Because precipitation is influenced by various atmospheric variables, it is highly nonlinear. Although precipitation predicted by a dynamic model can be corrected by using a nonlinear Artificial Neural Network, this approach has limits such as choices of the initial weight, local minima and the number of neurons, etc. In the present paper, we correct simulated precipitation by using a multiple linear regression (MLR) method, which is simple and widely used. First of all, Ensemble hindcast is conducted by the PNU/CME Coupled General Circulation Model (CGCM) (Park and Ahn, 2004) for the period from April to August in 1979-2005. MLR is applied to precipitation simulated by PNU/CME CGCM for the months of June (lead 2), July (lead 3), August (lead 4) and seasonal mean JJA (from June to August) of the Northeast Asian region including the Korean Peninsula $(110^{\circ}-145^{\circ}E,\;25-55^{\circ}N)$. We build the MLR model using a linear relationship between observed precipitation and the hindcasted results from the PNU/CME CGCM. The predictor variables selected from CGCM are precipitation, 500 hPa vertical velocity, 200 hPa divergence, surface air temperature and others. After performing a leave-oneout cross validation, the results are compared with the PNU/CME CGCM's. The results including Heidke skill scores demonstrate that the MLR corrected results have better forecasts than the direct CGCM result for rainfall.

• Journal of the Korean earth science society
• /
• v.30 no.3
• /
• pp.294-304
• /
• 2009

A statistical prediction model for the typhoon intensity and track in the Northwestern Pacific area was developed based on the artificial neural network scheme. Specifically, this model is focused on the 5-day prediction after tropical cyclone genesis, and used the CLIPPER parameters (genesis location, intensity, and date), dynamic parameters (vertical wind shear between 200 and 850hPa, upper-level divergence, and lower-level relative vorticity), and thermal parameters (upper-level equivalent potential temperature, ENSO, 200-hPa air temperature, mid-level relative humidity). Based on the characteristics of predictors, a total of seven artificial neural network models were developed. The best one was the case that combined the CLIPPER parameters and thermal parameters. This case showed higher predictability during the summer season than the winter season, and the forecast error also depended on the location: The intensity error rate increases when the genesis location moves to Southeastern area and the track error increases when it moves to Northwestern area. Comparing the predictability with the multiple linear regression model, the artificial neural network model showed better performance.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.996-1000
• /
• 2009

물순환계를 종합적으로 관리하기 위해서는 물순환계의 모니터링과 해석모형의 구축이 필요하다. 실측자료만으로는 복잡 다양한 물순환계 구조 및 인과관계를 규명할 수 없기 때문에 시간적 공간적으로 변화하는 다양한 수문현상을 일관된 하나의 시스템으로 이해하기 위해 물순환 해석모델을 구축하여 검토할 필요가 있다. CAT(Catchment hydrologic cycle Analysis Tool)은 수문학적으로 균일하게 판단되는 범위를 소유역으로 분할하여 지형학적 요인에 의한 유출 특성을 객관적으로 반영할 수 있게 하며, 토양층에 따라 침투, 증발, 지하수 흐름 등의 모의가 가능하도록 하는 Link-Node 모형으로, 증발산은 기준 증발산을 외부에서 직접 입력하거나, Penman-Monteith 방법을 선택할 수 있으며, 침투는 토양의 수리전도도에 따른 연직방향 침투 및 사면방향 복귀류를 고려할 수 있다. 노드의 지하수 유거를 고려하여 기존 노드-링크 방식 모형의 장기 유출 해석시 제한점을 보완하였으며, Muskingum, Muskingum-Cunge, Kinematic wave 방법을 이용하여 하도추적을 모의할 수 있다. 또한 GUI를 통해 사용자가 손쉽게 모형을 적용하고 관리 할 수 있도록 하고, 여러 시나리오를 적용함에 있어서 편리하도록 개발 중인 모형이다. 본 연구에서는 개발중인 CAT 모형을 평가 하기위해 시험 유역으로 운영 중인 설마천 유역에 적용하여 소유역 분할(노드수), 계산 시간 간격(일/시단위) 등에 따른 적용성을 평가하였다. 관측 자료를 통해 구축 가능한 물리적 매개변수를 통해 해당 유역을 단일 노드 및 다중 노드로 간단히 모형화할 수 있었으며, 모의 결과, 관측 유량과 적절히 일치하는 결과를 얻을 수 있었다. 1시간 단위에 대한 모의에서도 유출을 적절히 모의할 수 있었으며, 소규모 유역에 대한 정밀한 물순환 해석이 가능할 것으로 평가되었다.

• Korean Journal of Remote Sensing
• /
• v.35 no.5_1
• /
• pp.727-736
• /
• 2019

In this paper, we present how to create a point cloud for a target area using multiple unmanned aerial vehicle images and to remove the gaps and overlapping points between datasets. For this purpose, first, IBA (Incremental Bundle Adjustment) technique was applied to correct the position and attitude of UAV platform. We generate a point cloud by using MDR (Multi-Dimensional Relaxation) matching technique. Next, we register point clouds based on observation vectors between stereo images by doing this we remove gaps between point clouds which are generated from different stereo pairs. Finally, we applied an occupancy grids based integration algorithm to remove duplicated points to create an integrated point cloud. The experiments were performed using UAV images, and our experiments show that it is possible to remove gaps and duplicate points between point clouds generated from different stereo pairs.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.12 no.4
• /
• pp.277-288
• /
• 2010

The multi-level $H_2O/CO_2$ profile system has been widely used to quantify the storage and advection effects on energy and mass fluxes measured by eddy covariance systems. In this study, we expanded the utility of the profile system by accommodating air sampling devices for isotope analyses of water vapor and $CO_2$. A pre-evacuated 2L glass flask was connected to the discharge of an Infrared Gas Analyzer (IRGA) of the profile system so that airs with known concentration of $H_2O$ and $CO_2$ can be sampled. To test the performance of this sampling system, we sampled airs from 8 levels (from 0.1 to 40 m) at the KoFlux tower of Gwangneung deciduous forest, Korea. Air samples in the 2L flask were separated into its component gases and pure $H_2O$ and $CO_2$ were extracted by using a vacuum extraction line. This novel technique successfully produced vertical profiles of ${\delta}D$ of $H_2O$ and ${\delta}^{13}C$ of $CO_2$ in a mature forest, and estimated ${\delta}D$ of evapotranspiration (${\delta}D_{ET}$) and ${\delta}^{13}C$ of $CO_2$ from ecosystem respiration (${\delta}^{13}C_{resp}$) by using Keeling plots. While technical improvement is still required in various aspects, our sampling system has two major advantages over other proposed techniques. First, it is cost effective since our system uses the existing structure of the profile system. Second, both $CO_2$ and $H_2O$ can be sampled simultaneously so that net ecosystem exchange of $H_2O$ and $CO_2$ can be partitioned at the same temporal resolution, which will improve our understanding of the coupling between water and carbon cycles in terrestrial ecosystems.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_3
• /
• pp.1643-1652
• /
• 2020

To investigate the characteristics of detailed flows in a building-congested district, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. For realistic numerical simulations, we used the meteorological variables such as wind speeds and directions and potential temperatures predicted by LDAPS as the initial and boundary conditions of the CFD model. We trilinearly interpolated the horizontal wind components of LDAPS to provide the initial and boudnary wind velocities to the CFD model. The trilinearly interpolated potential temperatures of LDAPS is converted to temperatures at each grid point of the CFD model. We linearly interpolated the horizontal wind components of LDAPS to provide the initial and boundary wind velocities to the CFD model. The linearly interpolated potential temperatures of LDAPS are converted to temperatures at each grid point of the CFD model. We validated the simulated wind speeds and directions against those measured at the PKNU-SONIC station. The LDAPS-CFD model reproduced similar wind directions and wind speeds measured at the PKNU-SONIC station. At 07 LST on 22 June 2020, the inflow was east-north-easterly. Flow distortion by buildings resulted in the east-south-easterly at the PKNU-SONIC station, which was the similar wind direction to the measured one. At 19 LST when the inflow was southeasterly, the LDAPS-CFD model simulated southeasterly (similar to the measured wind direction) at the PKNU-SONIC station.