• Transactions on Control, Automation and Systems Engineering
• /
• 제3권1호
• /
• pp.43-50
• /
• 2001

In this paper, we propose the design procedure of advance Polynomial Neural Networks(PNN) architecture for optimal model identification of complex and nonlinear system. The proposed PNN architecture is presented as the generic and advanced type. The essence of the design procedure dwells on the Group Method of Data Handling(GMDH). PNN is a flexible neural architecture whose structure is developed through learning. In particular, the number of layers of the PNN is not fixed in advance but is generated in a dynamic way. In this sense, PNN is a self-organizing network. With the aid of three representative numerical examples, compari-sons show that the proposed advanced PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and generalization capabilities of model is evaluated and also discussed.

• 한국표면공학회지
• /
• 제36권1호
• /
• pp.69-73
• /
• 2003

The atmospheric pressure plasma is regarded as an effective method for surface treatments because it can reduce the period of process and doesn't need expensive vacuum apparatus. The performance of non-transferred plasma torches is significantly depended on jet flow characteristics out of the nozzle. In order to produce the high performance of a torch, the maximum discharge velocity near an annular gap in the torch should be maintained. Also, the compulsory swirl is being produced to gain the shape that can concentrate the plasma at the center of gas flow. In this work, the distribution of gas flow that goes out to atmosphere through a plenum chamber and nozzle is analyzed to evaluate the performance of atmospheric pressure plasma torch which can present the optimum design of the torch. Numerical analysis is carried out with various angles of an inlet flow velocity. Especially, three-dimensional model of the torch is investigated to estimate swirl effect. We also investigate the stabilization of plasma distribution. For analyzing the swirl in the plenum chamber and the flow distribution, FVM (finite volume method) and SIMPLE algorithm are used for solving the governing equations. The standard k-model is used for simulating the turbulence.

• 한국수소및신에너지학회논문집
• /
• 제27권1호
• /
• pp.127-134
• /
• 2016

Most of reconstruction algorithms for the calculation of temperature distributions in CT (computed tomography)-TDLAS (tunable diode laser absorption spectroscopy) are based upon two-line thermometry method. This method gives unstable calculation convergence due to signal noise, bias error, and signal mis-matches. In this study, a new reconstruction algorithm based on cross-correlation for temperature calculation is proposed. The patterns of the optical signals at all wave lengths were used to reconstruct the temperature distribution. Numerical test has been made using phantom temperature distributions. Using these phantom temperature data, absorption spectra for all wave lengths were constructed, and these spectra were regarded as the signals that would be obtained in an actual experiments. Using these virtually generated experimental signals, temperature distribution was once again reconstructed, and was compared with those of the original phantom data. Calculation errors obtained by the newly proposed algorithm were slightly large at high temperatures with small errors at low temperature.

• 한국항공우주학회지
• /
• 제49권5호
• /
• pp.365-372
• /
• 2021

본 논문에서는 가변 연속사격 시간을 고려한 근접 방어 시스템(Closed-In Weapon System, CIWS)의 최적 무장 할당 알고리듬에 대해 다룬다. 본 연구에서 근접 방어 시스템의 무장 할당 문제는 혼합정수계획법(Mixed Integer Linear Programming, MILP)을 기반으로 정식화된다. 제안한 방법은 연속사격 시간을 교전 사거리와 관계없이 일정하다고 가정한 기존 연구와 달리 사거리에 따른 요격확률을 바탕으로 가변 연속사격 시간을 고려한다. 따라서 기존의 방법대비 보다 현실적인 교전상황을 반영할 수 있을 뿐만 아니라 표적 대응시간을 향상할 수 있다. 본 논문에서는 가변연속사격 시간이 반영되도록 기존의 혼합정수계획법 기반 무장 할당 문제를 변형시켰으며, 상용최적화 프로그램을 활용한 수치 시뮬레이션을 통해 제안한 방법의 성능을 검증하였다.

• 한국수소및신에너지학회논문집
• /
• 제27권3호
• /
• pp.318-327
• /
• 2016

In order to improve the performance of temperature field measurements by CT-TDLAS (Computer Tomography Tunable Diode Laser Absorption Spectroscopy), a new reconstruction algorithm, named two-ratios-of-three-peaks method is proposed in this paper. Further, two methods for selecting appropriate initial values of the iterative calculation of CT-TDLAS are proposed. One is MLOS (multiplicative line of sight) method and the other one is ALOS (additive line of sight) method. Two-ratios-of-three-peaks (2R3P) algorithm combined with MART (multiplicative algebraic reconstruction technique) is finally developed for the enhancements of reconstructive calculations. The results have been compared with those obtained by the conventional one-ratio-of-two-peaks (1R2P) algorithm. In order to evaluate the performance of this algorithm, numerical test has been performed using phantom Gaussian temperature distributions with $11{\times}11$ square mesh. The performance of the constructed algorithm has been demonstrated by comparing the results obtained in actual burner experiments with those obtained by thermocouples. It has been verified that 2R3P algorithm with MART and MLOS showed best performance than that of 1R2P algorithm.

• 제어로봇시스템학회논문지
• /
• 제8권7호
• /
• pp.613-623
• /
• 2002

Ascent trajectory optimization and explicit guidance problems for a satellite launch vehicle with yaw maneuver in a 3-dimension are considered. The trajectory optimization problem with boundary conditions is formulated as a nonlinear programming problem by parameterizing the inertial pitch and yaw attitude control variables, and is solved by using the SQP algorithm. The flight constraints such as gravity-turn and range safety conditions are imposed. An explicit inertial guidance algorithm in the exoatmospheric phase is also presented. The guidance algorithm provides steering command and time-to-go value directly using the current states of the vehicle and the desired orbit insertion conditions. The liquid propelled Delta 2910 launch vehicle is used as a numerical model.

• 한국항행학회논문지
• /
• 제12권1호
• /
• pp.74-81
• /
• 2008

본 연구에서는 공간영역특성의 컬러정보와 주파수영역 기반의 시각특성 요소를 이용한 혼합 워터마킹 기법을 제안하였다. 제안한 방법은 공간영역을 선택하여 컬러의 색차 정보를 분석하여 공간적으로 분포되어있는 컬러정보를 계산하고, 주파수 변환영역을 통해 인간시각에 덜 민감한 계수블럭을 분석하여 인간의 시각특성 파라미터 값들을 구하였다. 또한 중요한 특징 중에 하나는 퍼지추론 기법을 시각시스템 특성에 적용하여 워터마크가 삽입될 최적의 부 대역을 선택하도록 설계하였다. 계수분포에 따른 적응적 워터마크를 삽입한 후, 비가시성과 강인성 평가 실험을 수행한 결과 다양한 종류의 공격유형에 대하여 제안한 방법의 타당성을 입증 하였다.

• Journal of Communications and Networks
• /
• 제16권2호
• /
• pp.121-129
• /
• 2014

The trend of an increasing demand for a high-quality user experience, coupled with a shortage of radio resources, has necessitated more advanced wireless techniques to cooperatively achieve the required quality-of-experience enhancement. In this study, we investigate the critical problem of rate splitting in heterogeneous cellular networks, where concurrent transmission, for instance, the coordinated multipoint transmission and reception of LTE-A systems, shows promise for improvement of network-wide capacity and the user experience. Unlike most current studies, which only deal with spectral efficiency enhancement, we implement an optimal rate splitting strategy to improve both spectral efficiency and energy efficiency by exploring and exploiting cooperation diversity. First, we introduce the motivation for our proposed algorithm, and then employ the typical cooperative bargaining game to formulate the problem. Next, we derive the best response function by analyzing the dual problem of the defined primal problem. The existence and uniqueness of the proposed cooperative bargaining equilibrium are proved, and more importantly, a distributed algorithm is designed to approach the optimal unique solution under mild conditions. Finally, numerical results show a performance improvement for our proposed distributed cooperative rate splitting algorithm.

• 콘크리트학회논문집
• /
• 제17권3호
• /
• pp.369-374
• /
• 2005

이 연구의 목적은 화상처리 기법과 신경회로망을 이용하여 다섯가지 균열 패턴 즉, 횡방향, 종방향, 대각선($-45^{\circ}$) 대각선($+45^{\circ}$) 그리고 비방향성 균열의 패턴을 인식할 수 있는 기법을 제안하는 것이다. 제안된 화상처리 알고리즘과 인공 신경회로망 모델은 MATLAB 언어를 이용하여 구현하였다. 인공 신경회로망의 입력층에 들어갈 패턴인자는 Total projection technique를 통해 구하였으며, 인공 신경회로망의 구조(은닉층의 수와 은닉노드의 수)와 가중치 값은 가상 균열 화상을 사용하여 학습을 통해 결정하였다. 인공 신경회로망의 학습은 Bayesian regularization 기법을 도입함으로써 과적합 문제가 발생하지 않도록 하였으며, 이 연구에서 제안한 기법의 적합성을 판정하기 위하여 총 38개의 실제 균열 화상을 사용하여 시험하였다. 검증 시험 결과내에서는 이 연구에서 제안한 기법이 사람의 균열 패턴 인식결과와 정확히 일치하는 결과것으로 나타났다.

• 대기
• /
• 제31권5호
• /
• pp.489-510
• /
• 2021

In this paper, we propose an algorithm for detecting convective initiation (CI) using GEO-KOMPSAT-2A/advanced meteorological imager data. The algorithm identifies clouds that are likely to grow into convective clouds with radar reflectivity greater than 35 dBZ within the next two hours. This algorithm is developed using statistical and qualitative analysis of cloud characteristics, such as atmospheric instability, cloud top height, and phase, for convective clouds that occurred on the Korean Peninsula from June to September 2019. The CI algorithm consists of four steps: 1) convective cloud mask, 2) cloud object clustering and tracking, 3) interest field tests, and 4) post-processing tests to remove non-convective objects. Validation, performed using 14 CI events that occurred in the summer of 2020 in Korean Peninsula, shows a total probability of detection of 0.89, false-alarm ratio of 0.46, and mean lead-time of 39 minutes. This algorithm can be useful warnings of rapidly developing convective clouds in future by providing information about CI that is otherwise difficult to predict from radar or a numerical prediction model. This CI information will be provided in short-term forecasts to help predict severe weather events such as localized torrential rainfall and hail.