• 제목/요약/키워드: Optimum Algorithm

검색결과 1,621건 처리시간 0.03초

Stream flow estimation in small to large size streams using Sentinel-1 Synthetic Aperture Radar (SAR) data in Han River Basin, Korea

  • Ahmad, Waqas;Kim, Dongkyun
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2019년도 학술발표회
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    • pp.152-152
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    • 2019
  • This study demonstrates a novel approach of remotely sensed estimates of stream flow at fifteen hydrological station in the Han River Basin, Korea. Multi-temporal data of the European Space Agency's Sentinel-1 SAR satellite from 19 January, 2015 to 25 August, 2018 is used to develop and validate the flow estimation model for each station. The flow estimation model is based on a power law relationship established between the remotely sensed surface area of water at a selected reach of the stream and the observed discharge. The satellite images were pre-processed for thermal noise, radiometric, speckle and terrain correction. The difference in SAR image brightness caused by the differences in SAR satellite look angle and atmospheric condition are corrected using the histogram matching technique. Selective area filtering is applied to identify the extent of the selected stream reach where the change in water surface area is highly sensitive to the change in stream discharge. Following this, an iterative procedure called the Optimum Threshold Classification Algorithm (OTC) is applied to the multi-temporal selective areas to extract a series of water surface areas. It is observed that the extracted water surface area and the stream discharge are related by the power law equation. A strong correlation coefficient ranging from 0.68 to 0.98 (mean=0.89) was observed for thirteen hydrological stations, while at two stations the relationship was highly affected by the hydraulic structures such as dam. It is further identified that the availability of remotely sensed data for a range of discharge conditions and the geometric properties of the selected stream reach such as the stream width and side slope influence the accuracy of the flow estimation model.

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Piecewise exact solution for analysis of base-isolated structures under earthquakes

  • Tsai, C.S.;Chiang, Tsu-Cheng;Chen, Bo-Jen;Chen, Kuei-Chi
    • Structural Engineering and Mechanics
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    • 제19권4호
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    • pp.381-399
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    • 2005
  • Base isolation technologies have been proven to be very efficient in protecting structures from seismic hazards during experimental and theoretical studies. In recent years, there have been more and more engineering applications using base isolators to upgrade the seismic resistibility of structures. Optimum design of the base isolator can lessen the undesirable seismic hazard with the most efficiency. Hence, tracing the nonlinear behavior of the base isolator with good accuracy is important in the engineering profession. In order to predict the nonlinear behavior of base isolated structures precisely, hundreds even thousands of degrees-of-freedom and iterative algorithm are required for nonlinear time history analysis. In view of this, a simple and feasible exact formulation without any iteration has been proposed in this study to calculate the seismic responses of structures with base isolators. Comparison between the experimental results from shaking table tests conducted at National Center for Research on Earthquake Engineering in Taiwan and the analytical results show that the proposed method can accurately simulate the seismic behavior of base isolated structures with elastomeric bearings. Furthermore, it is also shown that the proposed method can predict the nonlinear behavior of the VCFPS isolated structure with accuracy as compared to that from the nonlinear finite element program. Therefore, the proposed concept can be used as a simple and practical tool for engineering professions for designing the elastomeric bearing as well as sliding bearing.

Coupled solid and fluid mechanics simulation for estimating optimum injection pressure during reservoir CO2-EOR

  • Elyasi, Ayub;Goshtasbi, Kamran;Hashemolhosseini, Hamid;Barati, Sharif
    • Structural Engineering and Mechanics
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    • 제59권1호
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    • pp.37-57
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    • 2016
  • Reservoir geomechanics can play an important role in hydrocarbon recovery mechanism. In $CO_2$-EOR process, reservoir geomechanics analysis is concerned with the simultaneous study of fluid flow and the mechanical response of the reservoir under $CO_2$ injection. Accurate prediction of geomechanical effects during $CO_2$ injection will assist in modeling the Carbon dioxide recovery process and making a better design of process and production equipment. This paper deals with the implementation of a program (FORTRAN 90 interface code), which was developed to couple conventional reservoir (ECLIPSE) and geomechanical (ABAQUS) simulators, using a partial coupling algorithm. A geomechanics reservoir partially coupled approach is presented that allows to iteratively take the impact of geomechanics into account in the fluid flow calculations and therefore performs a better prediction of the process. The proposed approach is illustrated on a realistic field case. The reservoir geomechanics coupled models show that in the case of lower maximum bottom hole injection pressure, the cumulative oil production is more than other scenarios. Moreover at the high injection pressures, the production rates will not change with the injection bottom hole pressure variations. Also the FEM analysis of the reservoir showed that at $CO_2$ injection pressure of 11000 Psi the plastic strain has been occurred in the some parts of the reservoir and the related stress path show a critical behavior.

중수승급기 성능관리 프로그램 개발 (Computer Program Development for D$_2$O Upgrader Performance Management)

  • Ahn, Do-Hee;Kim, Kwang-Rag;Chung, Hong-Suck;Kim, Yong-Eak;Jeong, Ill-Seok;Hon, Sung-Yull;Ko, Jae-Wook
    • Nuclear Engineering and Technology
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    • 제22권1호
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    • pp.1-11
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    • 1990
  • 중수는 중수형 원자로의 감속재 및 냉각재로 사용되고 있으며 그 가격이 고가이기 때문에 일단 계통내에서 사용된 후 농도가 낮아진 저등급 중수는 중수승급기를 통해 99.8% 이상으로 농축 재생되어 중수로로 재주입되고 있다. 본 연구에서는 중수승급기의 공정을 면밀히 검토하였고 정상상태의 중수증류공정의 해석을 위하여 이론적인 모델을 제시하였으며 변수들간의 관계식을 설정하였다. 그리고 이 비선형 관계식을 단계적으로 처리하는 알고리즘의 전산 프로그램 UPGR을 개발하였다. 전산코드의 결과는 실제 운전 데이타와 잘 일치하였다. 월성 1호기에서 이를 이용한 운전지침의 제시, 운전효율의 평가, 성능평가 및 성능관리를 수행함으로써 중수승급기의 효율적인 운전에 기여하고 있다.

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Kalman Filter 복수 적용을 통한 Backprojection 기반 FMCW-SAR의 영상복원 품질평가 (Assessment of Backprojection-based FMCW-SAR Image Restoration by Multiple Implementation of Kalman Filter)

  • 송주영;김덕진;황지환;안상호;김준우
    • 대한원격탐사학회지
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    • 제37권5_3호
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    • pp.1349-1359
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    • 2021
  • SAR SLC 영상을 취득하기 위해 원시 자료로부터 BPA 기반 영상복원을 수행할 때 정확한 GNSS-INS 센서의 위치 및 속도 정보를 획득하는 것은 중요하다. BPA 기반 영상복원을 수행한 연구에서 기기 오차 보정을 위해 Kalman Filter를 적용하였으나, 대부분 1회 적용하여 효과적으로 오차를 제거하였는지 판단하기 어렵다. 본 연구에서는 GNSS-INS 센서의 위치 및 속도 정보에 Kalman Filter를 복수회 적용한 뒤 BPA를 이용하여 영상복원을 수행하여 기기 오차 보정에 효과적인 필터링 횟수를 평가하고자 하였다. 이를 위해 2회의 항공기 실험을 진행하여 SAR 원시 자료를 취득하였고, 이들에 해당하는 GNSS-INS 센서 정보에 대해 실질적이고 연속적으로 Kalman Filter를 적용하였다. 본 연구를 통해 상이한 이동 경로를 가지는 GNSS-INS 정보가 상응하는 FMCW-SAR 영상의 BPA 기반 최적 영상복원에 필요한 Kalman Filter 적용 횟수에 영향을 미칠 수 있다는 것을 확인하였다.

수직축 풍력터빈 성능향상을 위한 풍력타워 최적설계에 관한 연구 (Optimum Design of a Wind Power Tower to Augment Performance of Vertical Axis Wind Turbine)

  • 조수용;임채환;조종현
    • 한국항공우주학회지
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    • 제47권3호
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    • pp.177-186
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    • 2019
  • 풍력 타워는 수직형 풍력터빈의 성능을 향상시키기 위해 사용되어왔다. 하지만 올바르게 설계되지 않은 풍력 타워는 오히려 풍력터빈의 성능을 저하시킬 수 있다. 따라서 본 연구에서는 풍력 타워의 최적화 연구를 수행하였다. 이를 위하여 다음과 같이 6가지의 설계변수가 선택되었다. 즉, 가이드 벽의 외부 및 내부 반경, 스플리터의 적용 여부, 스플리터의 내부 반경, 가이드 벽의 개수 및 원주각도가 선정되었다. 최적화를 위한 목적함수는 풍력타워 내에 설치된 수직형 풍력터빈에서의 주기적인 평균 토크가 사용되었으며, 최적화 과정에서 지엽적인 최적화 결과를 피하기 위하여 실험계획법, 유전자알고리즘 및 인공신경망기법이 사용되었다. 인공신경망은 세대의 증가에 따라 지속적으로 향상하였으며, 수직 풍력터빈의 성능은 독립운전에 비하여 최적화된 풍력 타워 내에서 두 배 이상 향상되었다.

Comparison of Recombination Methods ad Cooling Factors in Genetic Algorithms Applied to Folding of Protein Model System

  • 우수형;김두일;정선희
    • Bulletin of the Korean Chemical Society
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    • 제21권3호
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    • pp.281-290
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    • 2000
  • We varied recombination method of fenetic algorithm (GA), i.e., crossover step, to compare efficiency of these methods, and to find more optimum GA method. In one method (A), we select two conformations(parents) to be recombined by systematic combination of lowest energy conformations, and in the other (B), we select them in a ratio proportional to the energy of the conformation. Second variation lies in how to select crossover point. First, we select it randomly(1). Second, we select range of residues where internal energy of the molecule does not vary for more than two residues, select randomly among such regions, and we select either thr first (2a) or the second residue (2b) from the N-terminal side, or the first (2c) or the second residue (2d) from the C-terminal side in the selected region for crossover point. Third, we select longest such hregion, and select such residue(as cases 2) (3a, 3b, 3c or 3d) of the region. These methods were tested in a 2-dimensionl lattice system for 8 different sequences (the same ones used by Unger and Moult., 1993). Results show that compared to Unger and Moult's result(UM) which corresponds to B-1 case, our B-1 case performed similarly in overall. There are many cases where our new methods performed better than UM for some different sequences. When cooling factor affecting higher energy conformation to be accepted in Monte Carlo step was reduced, our B-1 and other cases performed better than UM; we found lower energy conformers, and found same energy conformers in a smaller steps. We discuss importance of cooling factor variation in Monte Carlo simulations of protein folding for different proteins. (A) method tends to find the minimum conformer faster than (B) method, and (3) method is superior or at least equal to (1) method.

Weight Adjustment Scheme Based on Hop Count in Q-routing for Software Defined Networks-enabled Wireless Sensor Networks

  • Godfrey, Daniel;Jang, Jinsoo;Kim, Ki-Il
    • Journal of information and communication convergence engineering
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    • 제20권1호
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    • pp.22-30
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    • 2022
  • The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

Decision based uncertainty model to predict rockburst in underground engineering structures using gradient boosting algorithms

  • Kidega, Richard;Ondiaka, Mary Nelima;Maina, Duncan;Jonah, Kiptanui Arap Too;Kamran, Muhammad
    • Geomechanics and Engineering
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    • 제30권3호
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    • pp.259-272
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    • 2022
  • Rockburst is a dynamic, multivariate, and non-linear phenomenon that occurs in underground mining and civil engineering structures. Predicting rockburst is challenging since conventional models are not standardized. Hence, machine learning techniques would improve the prediction accuracies. This study describes decision based uncertainty models to predict rockburst in underground engineering structures using gradient boosting algorithms (GBM). The model input variables were uniaxial compressive strength (UCS), uniaxial tensile strength (UTS), maximum tangential stress (MTS), excavation depth (D), stress ratio (SR), and brittleness coefficient (BC). Several models were trained using different combinations of the input variables and a 3-fold cross-validation resampling procedure. The hyperparameters comprising learning rate, number of boosting iterations, tree depth, and number of minimum observations were tuned to attain the optimum models. The performance of the models was tested using classification accuracy, Cohen's kappa coefficient (k), sensitivity and specificity. The best-performing model showed a classification accuracy, k, sensitivity and specificity values of 98%, 93%, 1.00 and 0.957 respectively by optimizing model ROC metrics. The most and least influential input variables were MTS and BC, respectively. The partial dependence plots revealed the relationship between the changes in the input variables and model predictions. The findings reveal that GBM can be used to anticipate rockburst and guide decisions about support requirements before mining development.

전역 최적 경로가 향상되지 않는 반복 탐색 횟수를 고려한 개미 집단 시스템 (Ant Colony System Considering the Iteration Search Frequency that the Global Optimal Path does not Improved)

  • 이승관;이대호
    • 한국컴퓨터정보학회논문지
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    • 제14권1호
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    • pp.9-15
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    • 2009
  • 개미 집단 시스템은 조합 최적화 문제를 해결하기 위한 메타 휴리스틱 탐색 방법이다. 기존 개미 집단시스템은 전역갱신과정에서 탐색된 전역 최적 경로에 대해서만 페로몬 갱신을 수행하는데, 전역 최적 경로가 탐색되지 않으면 페로몬 증발만 일어나며 주어진 종료 조건을 만족할 때까지 아무리 많은 반복 수행에도 페로몬 강화가 일어나지 않는다. 본 논문에서 제안된 개선된 개미 집단시스템은 전역 최적 경로의 길이가 주어진 반복 사이클 횟수 동안 더 이상 향상되지 못하면 국부최적에 빠졌다고 평가하고 상태전이 규칙에서 파라미터 감소를 통해 다음 노드를 선택하게 하였다. 이로 인해, 상태전이 규칙에서 파라미터 감소에 의한 다양화 전략으로 탐색하는 결과가 최적 경로 탐색뿐만 아니라, 평균 최적 경로 탐색과 평균 반복횟수의 성능이 우수함을 보여 주었으며, 실험을 통해 그 성능을 평가하였다.