• Journal of Environmental Impact Assessment
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• v.18 no.2
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• pp.99-109
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• 2009

In general, manual calibration is commonly used for the stream water quality modelling. Because the manual calibration depends upon the subjectivity and experience of the researcher, it has a problem with the objectivity of the modelling. Thus, the interest about the automatic calibration by the optimization technique is deeply increased. In this study, Influence coefficient algorithm and Genetic algorithm are introduced to develop an automatic calibration model for the QUAL2K that are the latest version of the QUAL2E. Genetic algorithm, used in this study, is very simple and easy to understand but also applicable to any complicated mathematical problem, and it can find out the global optimum solution effectively. The developed automatic calibration model is applied to the Gangneung Namdaecheon. The calibration results about the 11 water quality variables show the good correspondence between the calculated and observed water quality values.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.752-757
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• 2003

Recently, 3D structure recovery through self-calibration of camera has been actively researched. Traditional calibration algorithm requires known 3D coordinates of the control points while self-calibration only requires the corresponding points of images, thus it has more flexibility in real application. In general, self-calibration algorithm results in the nonlinear optimization problem using constraints from the intrinsic parameters of the camera. Thus, it requires initial value for the nonlinear minimization. Traditional approaches get the initial values assuming they have the same intrinsic parameters while they are dealing with the situation where the intrinsic parameters of the camera may change. In this paper, we propose new initialization method using the minimum 2 images. Proposed method is based on the assumption that the least violation of the camera’s intrinsic parameter gives more stable initial value. Synthetic and real experiment shows this result.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.4
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• pp.406-410
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• 2008

This paper presents a new robot calibration algorithm with joint stiffness parameters for the enhanced positioning accuracy of industrial robot manipulators. This work is towards on-going development of an industrial robot calibration software which is able to identify both the kinematic and non-kinematic robot parameters. In this paper, the conventional kinematic calibration and its important considerations are briefly described first. Then, a new robot calibration algorithm which simultaneously identifies both the kinematic and joint stiffness parameters is presented and explained through a computer simulation with a 2 DOF manipulator. Finally, the developed algorithm is implemented to Hyundai HX165 robot and its resulting improvement of the positioning accuracy is addressed.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.642-645
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• 2004

This paper focuses on recovering systematic biases during LIDAR calibration, particularly using natural surfaces as control features. Many previous approaches have utilized all the points overlapping with the control features and often experienced with an inaccurate value converged with a poor rate due to wrong correspondence in pairing a point and the corresponding control features. To overcome these shortcomings, we establish a preventive scheme to select the pairs of high confidence, where the confidence value is based on the error budget associated with the point measurement and the linearity and roughness of the control feature. This approach was then applied to calibraring the LIDAR data simulated with the given systematic biases. The parameters were successfully recovered using the proposed approach with the accuracy and convergence rate superior to those using the previous approaches.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.521-526
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• 2001

This research develops a low-cost and high accurate kinematic calibration method for a parallel typed machining center tool. A planar table is used for a mechanical fixture restricting the platform to place at the constrained pose and a low-cost and high accurate digital indicator is employed for a device checking if the constrained movement is satisfied within the established range. The kinematic parameters calibrated with respect to a single plane aren't influenced from the misalignment of the plane. A parameter observability is successfully obtained even through one planar constraint, which guarantees that the kinematic parameters is estimated by minimizing the cost function.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.3
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• pp.32-45
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• 1989

The positioning accuracy of robots depends upon a forward kinematics which relates the joint variables to the orientation and position of the robot extremity in the absolute coordinate system. The relationship between two connective joint coordi- nates of a robot, which is the basis of the kinematics, is defined by 4 Denavit-Hartenberg parameters. But manufacturing errors in machining and assembly process of robots lead to disctrepancies between the design parameters and the physical structure. Thus, improving the positioning accuracy of robots reguires the identification of the actual link parameters of each robot. In this study, the least-squares method is used to calibrate the link parameters and off-line parameter calibration software is developed. Computer simulation is done to study the dependence of the calibration performance upon the DOF of the robot and number of acquired data set used in the least-squares method. 3 DOF Robot/Controller and specially designed 3D coordinate measurer is made and experiment is carried out to verify the theoretical and computational analysis.

• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.1
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• pp.14-17
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• 2005

In this paper, an automated methodology for generating model parameters considering real manufacturing processes is presented with verified results. In addition, the outcomes of applications to the next generation of flash memory devices using the parameters calibrated from the process specification decision are analyzed. The test vehicle is replaced with a well-calibrated TCAD simulation. First, the calibration methodology is introduced and tested for a flash memory device. The calibration errors are less than 5% of a full chip operation, which is acceptable to designers. The results of the calibration are then used to predict the I-V curves and the model parameters of various transistors for the design of flash devices.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.1
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• pp.47-57
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• 2018

This study implemented the rainfall-runoff analysis of the Mekong River basin using the SWAT (Soil and Water Assessment Tool). The runoff analysis was simulated for 2000~2007, and 11 parameters were calibrated using the SUFI-2 (Sequential Uncertainty Fitting-version 2) algorithm of SWAT-CUP (Calibration and Uncertainty Program). As a result of analyzing optimal parameters and sensitivity analysis for 6 cases, the parameter ALPHA_BF was found to be the most sensitive. The reproducibility of the rainfall-runoff results decreased with increasing number of stations used for parameter calibration. The rainfall-runoff simulation results of Case 6 showed that the RMSE of Nong Khai and Kratie stations were 0.97 and 0.9, respectively, and the runoff patterns were relatively accurately simulated. The runoff patterns of Mukdahan and Khong Chaim stations were underestimated during the flood season from 2004 to 2005 but it was acceptable in terms of the overall runoff pattern. These results suggest that the combination of SWAT and SWAT-CUP models is applicable to very large watersheds such as the Mekong for rainfall-runoff simulation, but further studies are needed to reduce the range of modeling uncertainty.

• International Journal of Railway
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• v.9 no.1
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• pp.1-9
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• 2016

In order to achieve a comprehensive utilization of railway networks, it is necessary to accurately assess the timetable indicators that effect the train operation. This paper describes the parameter calibration for two timetable indicators: scheduled running time and scheduled dwell time. For the scheduled running time, an existing model is employed and the single timetable parameter (percentage of minimum running time) in that model is optimized. For the scheduled dwell time, two intrinsic characteristics: the significance of stations and the average headway at each station are proposed firstly to form a new model, and the corresponding timetable parameters (the weight of the significance and the weight of the average headway) are calibrated subsequently. The Floyd Algorithm is used to obtain the connectivity among stations, which represents the significance of the stations. A case study is conducted in a light rail transportation system with 17 underground stations. The results of this research show that the optimal value of the scheduled running time parameter can be automatically determined, and the proposed model for the scheduled dwell time works well with a high coefficient of determination and low relative root mean square error through the leave-one-out validation.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.287-287
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• 2023

Surface water-groundwater interaction (SWGI) is an important hydrological process that influences both the quantity and quality of water resources. However, regional scale SWGI model calibration and uncertainty analysis have been a challenge because integrated models inherently carry a vast number of parameters, modeling assumptions, and inputs, potentially leaving little time and budget to explore questions related to model performance and forecasting. In this study, we have proposed the application of iterative ensemble smoother (IES) for uncertainty analysis and calibration of the widely used integrated surface-subsurface model, SWAT-MODFLOW. SWAT-MODFLOW integrates Soil and Water Assessment Tool (SWAT) and a three-dimensional finite difference model (MODFLOW). The model was calibrated using a parameter estimation tool (PEST). The major advantage of the employed IES is that the number of model runs required for the calibration of an ensemble is independent of the number of adjustable parameters. The pilot point approach was followed to calibrate the aquifer parameters, namely hydraulic conductivity, specific storage, and specific yield. The parameter estimation process for the SWAT model focused primarily on surface-related parameters. The uncertainties both in the streamflow and groundwater level were assessed. The work presented provides valuable insights for future endeavors in coupled surface-subsurface modeling, data collection, model development, and informed decision-making.