• 제목/요약/키워드: Model validation

검색결과 3,155건 처리시간 0.036초

GA를 이용한 개선된 루프 형성법을 갖는 QFT 설계방법 (A Design Method of QFT with Improved Loop Shaping Approach using GA)

  • 김주식;이상혁;유정웅
    • 대한전기학회논문지:전력기술부문A
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    • 제48권8호
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    • pp.972-979
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    • 1999
  • QFT(Quantitative Feedback Theory) is a very practical design technique that emphasizes the use of feedback for achieving the desired system performance tolerances in despite of plant uncertainty and disturbance. The fundamental concept of QFT is a loop shaping procedure that a suitable controller can be found by shaping a nominal loop transfer function. The loop shaping synthesis involves the identification of a structure and the specialization of parameter optimization of a desired system. This paper presents an improved loop shaping approach of QFT with model validation using GA(Genetic Algorithm). The method presented in this paper removes the problems of iterative operation, transformation error, and model validation in the conventional methods without consideration of frequency domain.

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CROSS- VALIDATION OF LANDSLIDE SUSCEPTIBILITY MAPPING IN KOREA

  • LEE SARO
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.291-293
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    • 2004
  • The aim of this study was to cross-validate a spatial probabilistic model of landslide likelihood ratios at Boun, Janghung and Yongin, in Korea, using a Geographic Information System (GIS). Landslide locations within the study areas were identified by interpreting aerial photographs, satellite images and field surveys. Maps of the topography, soil type, forest cover, lineaments and land cover were constructed from the spatial data sets. The 14 factors that influence landslide occurrence were extracted from the database and the likelihood ratio of each factor was computed. 'Landslide susceptibility maps were drawn for these three areas using likelihood ratios derived not only from the data for that area but also using the likelihood ratios calculated from each of the other two areas (nine maps in all) as a cross-check of the validity of the method For validation and cross-validation, the results of the analyses were compared, in each study area, with actual landslide locations. The validation and cross-validation of the results showed satisfactory agreement between the susceptibility map and the existing landslide locations.

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Validation of UNIST Monte Carlo code MCS for criticality safety calculations with burnup credit through MOX criticality benchmark problems

  • Ta, Duy Long;Hong, Ser Gi;Lee, Deokjung
    • Nuclear Engineering and Technology
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    • 제53권1호
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    • pp.19-29
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    • 2021
  • This paper presents the validation of the MCS code for critical safety analysis with burnup credit for the spent fuel casks. The validation process in this work considers five critical benchmark problem sets, which consist of total 80 critical experiments having MOX fuels from the International Criticality Safety Benchmark Evaluation Project (ICSBEP). The similarity analysis with the use of sensitivity and uncertainty tool TSUNAMI in SCALE was used to determine the applicable benchmark experiments corresponding to each spent fuel cask model and then the Upper Safety Limits (USLs) except for the isotopic validation were evaluated following the guidance from NUREG/CR-6698. The validation process in this work was also performed with the MCNP6 for comparison with the results using MCS calculations. The results of this work showed the consistence between MCS and MCNP6 for the MOX fueled criticality benchmarks, thus proving the reliability of the MCS calculations.

딥러닝과 Char2Vec을 이용한 문장 유사도 판별 (The Sentence Similarity Measure Using Deep-Learning and Char2Vec)

  • 임근영;조영복
    • 한국정보통신학회논문지
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    • 제22권10호
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    • pp.1300-1306
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    • 2018
  • 본 연구는 자연어 처리 문제 중 하나인 문장 유사도 판별 문제를 딥러닝으로 해결하는 데에 있어 Char2Vec기반으로 문장을 전 처리하고 학습시켜 그 성능을 확인하고 대표적인 Word Embedding 모델 Word2Vec를 대체할 수 있는 가능성이 있는지 파악하고자 한다. 임의의 두 문장을 비교할 때 쓰는 딥러닝 구조로 Siamese Ma-STM 네트워크를 사용하였다. Word2Vec와 Char2Vec를 각각 기반으로 한 문장 유사도 판별 모델을 학습시키고 그 결과를 분석하였다. 실험 결과 Char2Vec를 기반으로 학습시킨 모델이 validation accuracy 75.1%을 보였고 Word2Vec를 기반으로 학습시킨 모델은 validation accuracy 71.6%를 보였다. 따라서 고 사양을 요구하는 Word2Vec대신 임베딩 레이어를 활용한 Char2Vec 기반의 전처리 모델을 활용함으로 분석 환경을 최적화 할 수 있다.

System Modeling and Robust Control of an AMB Spindle : Part I Modeling and Validation for Robust Control

  • Ahn, Hyeong-Joon;Han, Dong-Chul
    • Journal of Mechanical Science and Technology
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    • 제17권12호
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    • pp.1844-1854
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    • 2003
  • This paper discusses details of modeling and robust control of an AMB (active magnetic bearing) spindle, and part I presents a modeling and validation process of the AMB spindle. There are many components in AMB spindle : electromagnetic actuator, sensor, rotor, power amplifier and digital controller. If each component is carefully modeled and evaluated, the components have tight structured uncertainty bounds and achievable performance of the system increases. However, since some unknown dynamics may exist and the augmented plant could show some discrepancy with the real plant, the validation of the augmented plant is needed through measuring overall frequency responses of the actual plant. In addition, it is necessary to combine several components and identify them with a reduced order model. First, all components of the AMB spindle are carefully modeled and identified based on experimental data, which also render valuable information in quantifying structured uncertainties. Since sensors, power amplifiers and discretization dynamics can be considered as time delay components, such dynamics are combined and identified with a reduced order. Then, frequency responses of the open-loop plant are measured through closed-loop experiments to validate the augmented plant. The whole modeling process gives an accurate nominal model of a low order for the robust control design.

실차 실험을 통한 운전자 조향 모델의 검증 (Validation of Driver Steering Model with Vehicle Test)

  • 정태영;이건복;이경수
    • 한국자동차공학회논문집
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    • 제13권1호
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    • pp.76-82
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    • 2005
  • In this paper, validation of Driver Steering Model has been conducted. The comparison between the simulation model and vehicle test results shows that the model is very feasible for describing combined human driver and actual vehicle dynamic behaviors. The 3D vehicle model is consisted of 6-DOF sprung mass and 4-quarter car model for vehicle body dynamics. Powertrain model including differential gear and Pacejka tire model are applied. The driver steering model is also validated with vehicle test result. The driver steering model is based on angle and displacement error from the desired path, recognized by driver.

Subset 샘플링 검증 기법을 활용한 MSCRED 모델 기반 발전소 진동 데이터의 이상 진단 (Anomaly Detection In Real Power Plant Vibration Data by MSCRED Base Model Improved By Subset Sampling Validation)

  • 홍수웅;권장우
    • 융합정보논문지
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    • 제12권1호
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    • pp.31-38
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    • 2022
  • 본 논문은 전문가 독립적 비지도 신경망 학습 기반 다변량 시계열 데이터 분석 모델인 MSCRED(Multi-Scale Convolutional Recurrent Encoder-Decoder)의 실제 현장에서의 적용과 Auto-encoder 기반인 MSCRED 모델의 한계인, 학습 데이터가 오염되지 않아야 된다는 점을 극복하기 위한 학습 데이터 샘플링 기법인 Subset Sampling Validation을 제시한다. 라벨 분류가 되어있는 발전소 장비의 진동 데이터를 이용하여 1) 학습 데이터에 비정상 데이터가 섞여 있는 상황을 재현하고, 이를 학습한 경우 2) 1과 같은 상황에서 Subset Sampling Validation 기법을 통해 학습 데이터에서 비정상 데이터를 제거한 경우의 Anomaly Score를 비교하여 MSCRED와 Subset Sampling Validation 기법을 유효성을 평가한다. 이를 통해 본 논문은 전문가 독립적이며 오류 데이터에 강한 이상 진단 프레임워크를 제시해, 다양한 다변량 시계열 데이터 분야에서의 간결하고 정확한 해결 방법을 제시한다.

CROSS-VALIDATION OF ARTIFICIAL NEURAL NETWORK FOR LANDSLIDE SUSCEPTIBILITY ANALYSIS: A CASE STUDY OF KOREA

  • LEE SARO;LEE MOUNG-JIN;WON JOONG-SUN
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.298-301
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    • 2004
  • The aim of this study is to cross-validate of spatial probability model, artificial neural network at Boun, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the Boun, Janghung and Youngin areas from interpretation of aerial photographs, field surveys, and maps of the topography, soil type, forest cover and land use were constructed to spatial data-sets. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography, were calculated from the topographic database. Topographic type, texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter, age and density of forest were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using the landslide­occurrence factors by artificial neural network model. For the validation and cross-validation, the result of the analysis was applied to each study areas. The validation and cross-validate results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

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HSPF를 이용한 임하호 유역 유사량 모의 (Simulation of Sediment Yield from Imha Watershed Using HSPF)

  • 전지홍
    • 한국농공학회논문집
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    • 제52권6호
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    • pp.39-48
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    • 2010
  • Sediment yields from Imha watershed were simulated during 1993-2008 using Hydrologic Simulation Program-Fortran (HSPF). Using observed daily stream flow for 2004-2008 and hourly suspended solid concentration for three events during 2006, HSPF was calibrated and validated at the sites of Imha and Youngyang for stream flow and Dongchun and Jangpachun for sediment yield. The calibration and validation results represented high model efficiency for simulating daily stream flow and hourly suspended solid. The determination coefficients of calibration and validation were 0.90 and 0.81 for daily stream flow, and 0.91 and 0.86 for monthly stream flow, respectively. Based on model tolerances for calibration and validation of stream flow, HSPF performance for simulating stream flow represented 'very good'. The determination coefficients of calibration and validation were 0.94-0.96 and 0.95 for hourly sediment yields, respectively. The average yearly sediment yield during 1993-2008 was 122,290 ton/year and most of sediment yield (77 % of total yield) were generated from June to August. The calibrated HSPF simulated well the movement of water and eroded soil within Imha watershed.

교통사고모형 개발에서의 함수식 도출 방법론에 관한 연구 (Methodology for Determining Functional Forms in Developing Statistical Collision Models)

  • 백종대;험머 조셉
    • 한국도로학회논문집
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    • 제14권5호
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    • pp.189-199
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    • 2012
  • PURPOSES: The purpose of this study is to propose a new methodology for developing statistical collision models and to show the validation results of the methodology. METHODS: A new modeling method of introducing variables into the model one by one in a multiplicative form is suggested. A method for choosing explanatory variables to be introduced into the model is explained. A method for determining functional forms for each explanatory variable is introduced as well as a parameter estimating procedure. A model selection method is also dealt with. Finally, the validation results is provided to demonstrate the efficacy of the final models developed using the method suggested in this study. RESULTS: According to the results of the validation for the total and injury collisions, the predictive powers of the models developed using the method suggested in this study were better than those of generalized linear models for the same data. CONCLUSIONS: Using the methodology suggested in this study, we could develop better statistical collision models having better predictive powers. This was because the methodology enabled us to find the relationships between dependant variable and each explanatory variable individually and to find the functional forms for the relationships which can be more likely non-linear.