• 한국농공학회논문집
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• 제54권6호
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• pp.111-119
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• 2012

Applicability of 8 day interval flow data for the calibration of hydrologic model was evaluated using Hydrological Simulation Program-Fortran (HSPF) at Kyungan watershed. The 8 day interval flow monitored by Ministry of Environment located at upstream was calibrated and periodically validated during 2004-2008. And continuous daily flow monitored by Ministry of Construction & Transportation (MOCT) and located at the mouth was compared with daily simulated data during 2004-2007 as spatial validation. Automatic calibration tool which is Model-Independent Parameter Estimation & Uncertainty Analysis (PEST) was applied for HSPF calibration procedure. The model efficiencies for calibration and periodic validation were 0.63 and 0.88, and model performances were fair and very good, respectively, based on criteria of calibration tolerances. Continuous daily stream flow at the mouth of Kyungan watershed were good agreement with observed continuous daily stream flow with showing 0.63 NS value. The PEST program is very useful tool for HSPF hydrologic calibration using non-continuous daily stream flow as well as continuous daily stream flow. The 8 day interval flow data monitored by MOE could be used to calibrate hydrologic model if the continuous daily stream flow is unavailable.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2923-2925
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• 1999

The objective of camera calibration is to determine the internal optical characteristics of camera and 3D position and orientation of camera with respect to the real world. Calibration procedure applicable to general purpose cameras and lenses. The general method to revise the accuracy rate of calibration is using mathematical distortion of lens. The effective og calibration show big difference in proportion to distortion of camera lens. In this paper, we propose the method which calibration distortion model by using neural network. The neural network model implicity contains all the distortion model. We can predict the high accuracy of calibration method proposed in this paper. Neural network can set properly the distortion model which has difficulty to estimate exactly in general method. The performance of the proposed neural network approach is compared with the well-known Tsai's two stage method in terms of calibration errors. The results show that the proposed approach gives much more stable and acceptabke calibration error over Tsai's two stage method regardless of camera resolution and camera angle.

• Nuclear Engineering and Technology
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• 제49권6호
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• pp.1219-1225
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• 2017

In this work, a scalable algorithm for model calibration in nuclear engineering applications is presented and tested. The algorithm relies on the construction of surrogate models to replace the original model within the region of interest. These surrogate models can be constructed efficiently via reduced order modeling and subspace analysis. Once constructed, these surrogate models can be used to perform computationally expensive mathematical analyses. This work proposes a surrogate based model calibration algorithm. The proposed algorithm is used to calibrate various neutronics and thermal-hydraulics parameters. The virtual environment for reactor applications-core simulator (VERA-CS) is used to simulate a three-dimensional core depletion problem. The proposed algorithm is then used to construct a reduced order model (a surrogate) which is then used in a Bayesian approach to calibrate the neutronics and thermal-hydraulics parameters. The algorithm is tested and the benefits of data assimilation and calibration are highlighted in an uncertainty quantification study and requantification after the calibration process. Results showed that the proposed algorithm could help to reduce the uncertainty in key reactor attributes based on experimental and operational data.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2011년도 학술발표회
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• pp.19-19
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• 2011

The appraisals of hydrology model behavior for flow and water quality are generally performed through comparison of simulated data with observed ones. To perform appraisal of hydrology model, some criteria are often used, such as coefficient of determination ($R^2$), Nash and Sutcliffe model efficiency coefficient (NSE), index of agreement (d), modified forms of NSE and d, and relative efficiency criteria NSE and d. These criteria are used not only for hydrology model estimations also for various comparisons of two data sets; This NSE has been often used for SWAT calibration. However, it has been known that the NSE value has some limitations in evaluating hydrology at watersheds under monsoon climate because this statistic is largely affected by higher values in the data set. To overcome these limitations, the SWAT auto-calibration module was enhanced with K-means clustering and direct runoff/baseflow modules. However the NSE is still being used in this module to evaluate model performance. Therefore, the SWAT Auto-calibration module was modified to incorporate alternative efficiency criteria into the SWAT K-means/direct runoff-baseflow auto-calibration module. It is expected that this enhanced SWAT auto-calibration module will provide better calibration capability of SWAT model for all flow regime.

• 센서학회지
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• 제13권1호
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• pp.27-34
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• 2004

Camera calibration is an important and fundamental procedure for the application of a vision sensor to 3D problems. Recently many camera calibration methods have been proposed particularly in the area of robot vision. However, the reliability of data used in calibration has been seldomly considered in spite of its importance. In addition, a camera model can not guarantee good results consistently in various conditions. This paper proposes methods to overcome such uncertainty problems of data and camera models as we often encounter them in practical camera calibration steps. By the use of the RANSAC (Random Sample Consensus) algorithm, few data having excessive magnitudes of errors are excluded. Artificial neural networks combined in a two-step structure are trained to compensate for the result by a calibration method of a particular model in a given condition. The proposed methods are useful because they can be employed additionally to most existing camera calibration techniques if needed. We applied them to a linear camera calibration method and could get improved results.

• Near Infrared Analysis
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• 제1권1호
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• pp.1-7
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• 2000

A convenient algorithm for optimizing wavelength selection in multiple linear regression (MLR) has been developed. MOP (MLP Optimization Program) has been developed to test all possible MLR calibration models in a given spectral range and finally find an optimal MLR model with external validation capability. MOP generates all calibration models from all possible combinations of wavelength, and simultaneously calculates SEC (Standard Error of Calibration) and SEV (Standard Error of Validation) by predicting samples in a validation data set. Finally, with determined SEC and SEV, it calculates another parameter called SAD (Sum of SEC, SEV, and Absolute Difference between SEC and SEV: sum(SEC+SEV+Abs(SEC-SEV)). SAD is an useful parameter to find an optimal calibration model without over-fitting by simultaneously evaluating SEC, SEV, and difference of error between calibration and validation. The calibration model corresponding to the smallest SAD value is chosen as an optimum because the errors in both calibration and validation are minimal as well as similar in scale. To evaluate the capability of MOP, the determination of benzene content in unleaded gasoline has been examined. MOP successfully found the optimal calibration model and showed the better calibration and independent prediction performance compared to conventional MLR calibration.

• 한국정밀공학회지
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• 제14권4호
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• pp.64-71
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• 1997

Objective of calibration is to find out the accurate kinematic relationships between robot joint angles and the position of the end-effector by estimating accurate model parameters defining the kinematic function. Estimating the model parameters requires measurement of the end-effector position at a number of different robot configurations. This paper studies the implication of measurement configurations in robot calibration. For selecting appropriate measurement configurations in robot calibration, an index is defined to measure the observability of the model parameters with respect to a set of robot configurations. It is found that, as the observability index of the selected measurement configurations increase the attribution of the position errors to the parameter errors becomes dominant while the effects of the measurement and unmodeled errors are less significant; consequently better estimation of parameter errors is expected. To demonstrate the implication of the observability measure in robot calibration, computer simulations are performed and their results are discussed.

• 방사선산업학회지
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• 제17권4호
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• pp.471-479
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• 2023

In In-situ radioactivity measurement techniques, efficiency calibration models use predefined models to simulate a sample's geometry and radioactivity distribution. However, simplified efficiency calibration models lead to uncertainties in the efficiency curves, which in turn affect the radioactivity concentration results. This study aims to develop an efficiency calibration optimization methodology to improve the accuracy of in-situ gamma radiation measurements for byproducts from industrial facilities. To accomplish the objective, a drive mechanism for rotational measurement of an byproduct simulator and a sample was constructed. Using ISOCS, an efficiency calibration model of the designed object was generated. Then, the sensitivity analysis of the efficiency calibration model was performed, and the efficiency curve of the efficiency calibration model was optimized using the sensitivity analysis results. Finally, the radiation concentration of the simulated subject was estimated, compared, and evaluated with the designed certification value. For the sensitivity assessment of the influencing factors of the efficiency calibration model, the ISOCS Uncertainty Estimator was used for the horizontal and vertical size and density of the measured object. The standard deviation of the measurement efficiency as a function of the longitudinal size and density of the efficiency calibration model decreased with increasing energy region. When using the optimized efficiency calibration model, the measurement efficiency using IUE was improved compared to the measurement efficiency using ISOCS at the energy of ²²⁸Ac (911 keV) for the nuclide under analysis. Using the ISOCS efficiency calibration method, the difference between the measured radiation concentration and the design value for each simulated subject measurement direction was 4.1% (1% to 10%) on average. The difference between the estimated radioactivity concentration and the design value was 3.6% (1~8%) on average when using the ISOCS IUE efficiency calibration method, which was closer to the design value than the efficiency calibration method using ISOCS. In other words, the estimated radioactivity concentration using the optimized efficiency curve was similar to the designed radioactivity concentration. The results of this study can be utilized as the main basis for the development of regulatory technologies for the treatment and disposal of waste generated during the operation, maintenance, and facility replacement of domestic byproduct generation facilities.

• ETRI Journal
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• 제26권6호
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• pp.605-614
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• 2004

In this paper, we investigate array calibration algorithms to derive a further improved version for correcting antenna array errors and RF transceiver errors in CDMA smart antenna systems. The structure of a multi-channel RF transceiver with a digital calibration apparatus and its calibration techniques are presented, where we propose a new RF receiver calibration scheme to minimize interference of the calibration signal on the user signals. The calibration signal is injected into a multi-channel receiver through a calibration signal injector whose array response vector is controlled in order to have a low correlation with the antenna response vector of the receive signals. We suggest a model-based antenna array calibration to remove the antenna array errors including mutual coupling errors or to predict the element patterns from the array manifold measured at a small number of angles. Computer simulations and experiment results are shown to verify the calibration algorithms.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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• pp.85-90
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• 2005

This paper proposes the calibration procedure for stratified Warner's randomized response model, which suggested by Kim and Warde (2004). It is shown that the proposed calibration estimator is more efficient than the Kim and Warde's model.