• 지구물리
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• 제7권4호
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• pp.237-245
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• 2004

밀도 검층에 미치는 각 영향 요소들을 검토하고 현행 사용자 보정의 한계와 문제점 파악을 위한 기초 실험이 수행되었다. 간접 보정 방법에 속하는 현행 사용자 보정을 물과 알루미늄 블럭을 사용하는 사용자 보정과 반감기 식을 이용한 사용자 보정으로 구분하여 분석하였으며 국내에서 처음 시도된 지구물리모형 시추공을 이용한 직접 보정 방법의 적용 결과와 비교, 분석되었고 이로부터 기존의 사용자 보정의 한계와 가능성을 평가할 수 있었다.

• 대한교통학회지
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• 제29권1호
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• pp.113-123
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• 2011

미시적 시뮬레이션 모형은 컴퓨터 성능이 향상되고 정교한 모형이 개발되면서 광역적인 범위까지 적용분야가 점차 확대되고 있다. 현장 교통상황을 정확하게 묘사하기 위해서는 시뮬레이션 모형의 정확한 정산이 매우 중요하다. 국내에서는 거시적 모형에 대한 정산연구는 많이 진행된 반면에 미시적 모형에 대한 정산연구는 매우 부족한 실정이다. 본 연구에서는 유전자알고리즘 이용하여 미시적 시뮬레이션 모형의 파라미터를 자동으로 최적화하는 자동정산 체계를 제시하였다. 내부순환로 지점검지기에서 수집되는 관측교통량과 미시적 시뮬레이션모형(VISSIM)의 교통량 간의 제곱오차(RMSE)를 성능지표로 하고, 최적화 목적함수는 제곱오차를 최소화 하는 것으로 설정하였다. 내부순환로에 적용한 결과, 기본 파라미터에 비해 자동정산체계의 RMSE가 60.4%($19.3{\longrightarrow}7.6$)나 감소하여 매우 효과적인 것으로 나타났다.

• 한국물환경학회지
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• 제36권6호
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• pp.568-580
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• 2020

Calibrating a conceptual hydrologic model necessitates selection of a calibration period that produces the most reliable prediction. This often must be chosen randomly, however, since there is no objective guidance. Observation plays the most important role in the calibration or uncertainty evaluation of hydrologic models, in which the key factors are the length of the data and the hydro-climate conditions in which they were collected. In this study, we investigated the effect of the calibration period selected on the predictive performance and uncertainty of a model. After classifying the inflows of the Hapcheon Dam from 1991 to 2019 into four hydro-climate conditions (dry, wet, normal, and mixed), a conceptual hydrologic partitioning model was calibrated using data from the same hydro-climate condition. Then, predictive performance and post-parameter statistics were analyzed during the verification period under various hydro-climate conditions. The results of the study were as follows: 1) Hydro-climate conditions during the calibration period have a significant effect on model performance and uncertainty, 2) calibration of a hydrologic model using data in dry hydro-climate conditions is most advantageous in securing model performance for arbitrary hydro-climate conditions, and 3) the dry calibration can lead to more reliable model results.

• 로봇학회논문지
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• 제17권2호
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• pp.183-190
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• 2022

Accurate kinematic parameters of mobile robots are essential because inaccurate kinematic model produces considerable uncertainties on its odometry and control. Especially, kinematic parameters of caster type mobile robots are important due to their complex kinematic model. Despite the importance of accurate kinematic parameters for caster type mobile robots, few research dealt with the calibration of the kinematic model. Previous study proposed a calibration method that can only calibrate double-wheeled caster type mobile robot and requires direct-measuring of robot center point and distance between casters. This paper proposes a calibration method based on geometric approach that can calibrate single-wheeled caster type mobile robot with two or more casters, does not require direct-measuring, and can successfully acquire all kinematic parameters required for control and odometry. Simulation and hardware experiments conducted in this paper validates the proposed calibration method and shows its performance.

• Near Infrared Analysis
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• 제2권1호
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• pp.55-58
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• 2001

The object of this work was to investigate the influence of growing district and harvest year on calibration for sweetness (Brix) determination of Fuji apple fruit using near infrared (NIR) reflectance spectroscopy, and to develop the robust calibration across these variation. The calibration models was based on wavelength range of 1100∼2500 nm using a stepwise multiple linear regression. A calibration model by sample set of one growing district was not transferable to other growing districts. The combined calibration (data of three growing districts) predicted reasonable well against a population set drawn from all growing districts (SEP=0.69, Bias=0.075). A calibration model by sample set of one harvest year was not also transferable to other harvest years. The combined calibration (data of three harvest years) predicted well against a population set drawn from all harvest years (SEP=0.53, Bias=0.004).

• 전자공학회논문지B
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• 제30B권11호
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• pp.84-92
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• 1993

Calibration of Engine models is a painstaking process but very important for successful application to automotive industry problems. A combined heuristic and machine learning approach has therefore been adopted to improve the efficiency of model calibration. We developed an intelligent calibration program called ICALIB. It has been used on a daily basis for engine model applications, and has reduced the time required for model calibrations from many hours to a few minutes on average. In this paper, we describe the heuristic control strategies employed in ICALIB such as a hill-climbing search based on a state distance estimation function, incremental problem solution refinement by using a dynamic tolerance window, and calibration target parameter ordering for guiding the search. In addition, we present the application of amachine learning program called GID3*for automatic acquisition of heuristic rules for ordering target parameters.

• 한국농공학회논문집
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• 제55권4호
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• pp.13-20
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• 2013

The purpose of this study was to evaluate the applicability of the HSPEXP expert system for the calibration of the Hydrological Simulation Program - Fortran (HSPF) for the study watershed. HSPEXP offers advice to the modeler, suggesting parameter changes that might result in better representation of a river basin and provides explanations supporting the recommended parameter changes. The study watershed, Sancheong, is located within the Nakdong River Basin and having the size of $1,072.4km^2$. Input data for the HSPF model were obtained from the landuse map, digital elevation map, meteorological data and others. Water flow data from 2006 to 2008 were used for calibration and from 2009 to 2010 were for validation. Using the HSPEXP expert system, hydrological parameters were adjusted based on total volume, then low flows, storm flows, and finally seasonal flows. For the calibration and validation period, all the HSPEXP model performance criteria were satisfied.

• 한국물환경학회지
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• 제25권3호
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• pp.432-440
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• 2009

The effect of selecting hydrologic item for calculating objective function on calibration of stream flow was evaluated by Hydrologic Simulation Porgram-Fortran (HSPF) linked with Model Independent Parameter Optimizer (PEST). Daily and monthly stream flow and flow duration were used to calculate objective function. Automated calibration focused on monthly stream was proper to analyze seasonal or yearly water budget but not proper to predict daily stream flow or percent chance flow exceeded. Calibration result focused on flow duration is proper to predict precent chance flow exceeded but not proper to analyze water budget or predict peak flow. These results indicate that hydrologic item calculated for objective function on calibration procedure could influence calibration results and watershed modeler should select carefully hydrologic item for the purpose of model application. Current, the criteria of stream flow of Korean TMDL is generated based on percent chance flow exceeded, so flow duration should be included to calculate objective function on calibration procedure for the estimation of criteria of stream flow using hydrologic model.

• 한국수자원학회논문집
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• 제39권8호
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• pp.677-690
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• 2006

본 연구에서는 LH-OAT (Latin Hypercube Ore factor At a Time) 민감도분석 방법과 SCE-UA (Shuffled Complex Evolution at University of Arizona) 최적화 기법을 적용하여 보청천 유역에서 SWAT모형에 대한 자동보정 방법을 제시하였다. LH-OAT 방법은 전역 민감도분석과 부분 민감도 분석의 장점을 조합하여 가용매개변수 공간에 대하여 효율적으로 매개변수의 민감도 분석이 가능하게 하였다. LH-OAT민감도 분석으로부터 결정된 매개변수의 민감도 등급은 SWAT 모형의 자동보정 과정에서 요구되는 보정대상 매개변수의 선택에 유용하게 적용될 수 있다. SCE-UA 방법을 적용한 SWAT모형의 자동보정 해석결과는 보정자료, 보정매개변수, 통계적 오차의 선택에 따라서 모형의 성능이 좌우되었다. 보정기간과 보정매개변수가 증가함에 따라 검증기간에 대한 RMSE (Root Mean Square Error), NSEF (Nash-Sutcliffe Model Efficiency), RMAE (Relative Mean Absolute Error), NMSE (Normalized Mean Square Error) 등의 모형오차는 감소하였지만, NAE (Normalized Average Error) 및 SDR(Standard Deviation Ratio)은 개선되지 않았다. SWAT모형의 보정에 적용되는 보정자료, 보정매개변수 및 모형평가를 위한 통계적 오차 선택이 해석결과에 미치는 복잡한 영향을 이해하기 위하여 다양한 대표유역을 대상으로 추가적인 연구가 필요하다.

• 환경영향평가
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• 제20권3호
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• pp.357-365
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• 2011

The QUAL2K has the same basic characteristics as the QUAL2E model, which has been widely used in stream water quality modeling; in QUAL2K, however, various functions are supplemented. The QUAL2Kw model uses a genetic algorithm(GA) for automatic calibration of QUAL2K, and it can search for optimum water quality parameters efficiently using the calculation results of the model. The QUAL2Kw model was applied to the Gangneung Namdaecheon River on the east side of the Korean Peninsula. Because of the effluents from the urban area, the middle and lower parts of the river are more polluted than the upper parts. Moreover, the hydraulic characteristics differ between the lower and upper parts of rivers. Thus, the river reaches were divided into seven parts, auto-calibration for the multiple reaches was performed using the function of the user-defined automatic calibration of the rates worksheets. Because GA parameters affect the optimal solution of the model, the impact of the GA parameters used in QUAL2Kw on the fitness of the model was analyzed. Sensitivity analysis of various factors, such as population size, crossover probability, crossover mode, strategy for mutation and elitism, mutation rate, and reproduction plan, were performed. Using the results of this sensitivity analysis, the optimum GA parameters were selected to achieve the best fitness value.