• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.3 s.43
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• pp.33-42
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• 2005

Frequency domain Volterra model is applied to nonlinear parameter identification procedure for dynamic systems modeled by nonlinear function. The frequency domain Volterra kernels, which correspond io linear, quadratic, and cubic transfer functions in lime domain, are incorporated in nonlinear parametric identification procedure. The nonlinear transfer functions, which can be derived from the Volterra series representation of the nonlinear differential equation of the system by Schetzen's method(1980), are directly used for modeling input output relation. The error is defined by the difference between the observed output and the estimated output which is calculated by substituting the observed input to nonlinear frequency domain model. The system parameters are searched by minimizing the error. Volterra model guarantees enough accuracy and convergence and the estimated coefficients have a good agreement with their actual values not only in the linear frequency region but also in the legion where the $2^{nd}\;or\;3^{rd}$ order nonlinearity is dominant.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.221-228
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• 2024

Predicting insurance claims is a key task for insurance companies to manage risks and maintain financial stability. Accurate insurance claim predictions enable insurers to set appropriate premiums, reduce unexpected losses, and improve the quality of customer service. This study aims to enhance the performance of insurance claim prediction models by applying ensemble learning techniques. The predictive performance of models such as Random Forest, Gradient Boosting Machine (GBM), XGBoost, Stacking, and the proposed Dynamic Weighted Ensemble (DWE) model were compared and analyzed. Model performance was evaluated using Mean Absolute Error (MAE), Mean Squared Error (MSE), and the Coefficient of Determination (R²). Experimental results showed that the DWE model outperformed others in terms of evaluation metrics, achieving optimal predictive performance by combining the prediction results of Random Forest, XGBoost, LR, and LightGBM. This study demonstrates that ensemble learning techniques are effective in improving the accuracy of insurance claim predictions and suggests the potential utilization of AI-based predictive models in the insurance industry.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.855-862
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• 1998

This paper investigates the impact of the forecast error on performance of a reservoir system for hydropower production. Forecast error is measured as th Root Mean Square Error (RMSE) and parametrically varied within a Generalized Maintenance Of Variance Extension (GMOVE) procedure. A set of transition probabilities are calculated as a function of the RMSE of the GMOVE procedure and then incorporated into a Bayesian Stochastic Dynamic Programming model which derives monthly operating policies and assesses their performance. As a case study, the proposed methodology is applied to the Skagit Hydropower System (SHS) in Washington state. The results show that the system performance is a nonlinear function of RMSE and therefor suggested that continued improvements in the current forecast accuracy correspond to gradually greater increase in performance of the SHS.

• Nuclear Engineering and Technology
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• v.49 no.8
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• pp.1696-1710
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• 2017

An improved Reactor Regulating System (RRS) logic architecture, which is combined with genetic algorithm (GA), is implemented in this work. It is devised to provide an optimal solution to the current RRS. The current system works desirably and has contributed to safe and stable nuclear power plant operation. However, during the ascent and descent section of the reactor power, the RRS output reveals a relatively high steady-state error, and the output also carries a considerable level of overshoot. In an attempt to consolidate conservatism and minimize the error, this work proposes to apply GA to RRS and suggests reconfiguring the system. Prior to the use of GA, reverse engineering is implemented to build a Simulink-based RRS model. Reengineering is followed to produce a newly configured RRS to generate an output that has a reduced steady-state error and diminished overshoot level. A full-scope APR1400 simulator is used to examine the dynamic behaviors of RRS and to build the RRS Simulink model.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.90-102
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• 2009

In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.

• International journal of steel structures
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• v.18 no.5
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• pp.1541-1559
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• 2018

This paper addresses the dynamic loading characteristics of the shock tube onto sandwich steel beams as an efficient and accurate alternative to time consuming and complicated fluid structure interaction using finite element modeling. The corrugated sandwich steel beam consists of top and bottom flat substrates of steel 1018 and corrugated cores of steel 1008. The corrugated core layers are arranged with non-uniform thicknesses thus making sandwich beam graded. This sandwich beam is analogous to a steel beam with web and flanges. Substrates correspond to flanges and cores to web. The stress-strain relations of steel 1018 at high strain rates are measured using the split-Hopkinson pressure. Both carbon steels are assumed to follow bilinear strain hardening and strain rate-dependence. The present finite element modeling procedure with an improved dynamic impulse loading assumption is validated with a set of shock tube experiments, and it provides excellent correlation based on Russell error estimation with the test results. Four corrugated graded steel core arrangements are taken into account for core design parameters in order to maximize mitigation of blast load effects onto the structure. In addition, numerical study of four corrugated steel core placed in a reverse order is done using the validated finite element model. The dynamic behavior of the reversed steel core arrangement is compared with the normal core arrangement for deflections, contact force between support and specimen and plastic energy absorption.

• Smart Structures and Systems
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• v.19 no.1
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• pp.39-46
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• 2017

Finite element model updating is very effective procedure to determine the uncertainty parameters in structural model and minimize the differences between experimentally and numerically identified dynamic characteristics. This procedure can be practiced with manual and automatic model updating procedures. The manual model updating involves manual changes of geometry and analyses parameters by trial and error, guided by engineering judgement. Besides, the automated updating is performed by constructing a series of loops based on optimization procedures. This paper addresses the ambient vibration based finite element model updating of long span reinforced concrete highway bridges using manual model updating procedure. Birecik Highway Bridge located on the $81^{st}km$ of Şanliurfa-Gaziantep state highway over Firat River in Turkey is selected as a case study. The structural carrier system of the bridge consists of two main parts: Arch and Beam Compartments. In this part of the paper, the arch compartment is investigated. Three dimensional finite element model of the arch compartment of the bridge is constructed using SAP2000 software to determine the dynamic characteristics, numerically. Operational Modal Analysis method is used to extract dynamic characteristics using Enhanced Frequency Domain Decomposition method. Numerically and experimentally identified dynamic characteristics are compared with each other and finite element model of the arch compartment of the bridge is updated manually by changing some uncertain parameters such as section properties, damages, boundary conditions and material properties to reduce the difference between the results. It is demonstrated that the ambient vibration measurements are enough to identify the most significant modes of long span highway bridges. Maximum differences between the natural frequencies are reduced averagely from %49.1 to %0.6 by model updating. Also, a good harmony is found between mode shapes after finite element model updating.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.138-138
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• 2000

In this paper, a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a prefilter, the inverse dynamic model of a system and a fuzzy logic controller. The prefilter prevents high frequency effects from the inverse dynamic model. The model of the system is characterized by a nonlinear equation with coulomb friction. The fuzzy logic controller regulates the error between the set-point and the system output which may be caused by disturbances and it simultaneously traces the change o( the reference input. The parameters of the model are estimated by a genetic a]gorithm. An experimental work on a DC motor system is carried out to illustrate the performance of the proposed controller

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.658-662
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• 1988

The performance of a strapdown attitude reference system(SDARS) under dynamic environments was analyzed by means of computer simulation. The study is aimed toward the performance evaluation in the presence of translational or angular vibration during 20 sec of flight time. The simulation was based on the error model of rate gyro, and Euler angle algorithm was employed to compute the attitude.

• Journal of Power System Engineering
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• v.5 no.4
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• pp.90-96
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• 2001

In this study, a robust controller to control pressure in a pneumatic pressure vessel considering dynamic characteristics of pneumatic transmission line is proposed. Dynamic characteristics of transmission line using compressible fluid is changed by the flowing states of the fluid. So, if the fixed gain controller is designed based on a fixed model, the performance of the control system could be destabilized or degraded. The controller designed in this study is composed of two parts. The one is to reject modelling error based on the disturbance observer, the other is to obtain the control performance. The control results with the designed controller show that the robustness of the control system is achieved regardless of the change of the model of the transmission line. Therefore, the designed controller can be utilized for the performance improvement of the pressure control system using compressible fluid such as air and gas