• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권3호
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• pp.163-172
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• 2016

Electric load forecasting is essential for effective power system planning and operation. Complex and nonlinear relationships exist between the electric loads and their exogenous factors. In addition, time-series load data has non-stationary characteristics, such as trend, seasonality and anomalous day effects, making it difficult to predict the future loads. This paper proposes a locally-weighted polynomial neural network (LWPNN), which is a combination of a polynomial neural network (PNN) and locally-weighted regression (LWR) for daily shortterm peak load forecasting. Model over-fitting problems can be prevented effectively because PNN has an automatic structure identification mechanism for nonlinear system modeling. LWR applied to optimize the regression coefficients of LWPNN only uses the locally-weighted learning data points located in the neighborhood of the current query point instead of using all data points. LWPNN is very effective and suitable for predicting an electric load series with nonlinear and non-stationary characteristics. To confirm the effectiveness, the proposed LWPNN, standard PNN, support vector regression and artificial neural network are applied to a real world daily peak load dataset in Korea. The proposed LWPNN shows significantly good prediction accuracy compared to the other methods.

• Journal of Mechanical Science and Technology
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• 제15권6호
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• pp.709-719
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• 2001

In particle or short-fiber reinforced composites, cracking of reinforcements is a significant damage mode because the cracked reinforcements lose carrying capacity. This paper deals with elastic stress distributions and load carrying capacity of intact and cracked ellipsoidal inhomogeneities. Three dimensional finite element analysis has been carried out on intact and cracked ellipsoidal inhomogeneities in an infinite body under uniaxial tension and pure shear. For the intact inhomogeneity, as well known as Eshelbys solution, the stress distribution is uniform in the inhomogeneity and nonuniform in the surrounding matrix. On the other hand, for the cracked inhomogeneity, the stress in the region near the crack surface is considerably released and the stress distribution becomes more complex. The average stress in the inhomogeneity represents its load carrying capacity, and the difference between the average stresses of the intact and cracked inhomogeneities indicates the loss of load carrying capacity due to cracking damage. The load carrying capacity of the cracked inhomogeneity is expressed in to cracking damage. The load carrying capacity of the cracked inhomogeneity is expressed in terms of the average stress of the intact inhomogeneity and some coefficients. It is found that a cracked inhomogeneity with high aspect ratio still maintains higher load carrying capacity.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권3호
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• pp.117-123
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• 2000

A new control method for precision robust position control of a PMSM (Permanent Magnet Synchronous Motor) using asymptotically stable adaptive load torque observer is presented in the paper. Precision position control is obtained for the PMSM system approximately linearized using the field-orientation method. Recently, many of these drive systems use the PMSM to avoid backlashes. However, the disadvantages of the motor are high cost and complex control because of nonlinear characteristics. Also, the load torque disturbance directly affects the motor shaft. The application of the load torque observer is published in [1] using fixed gain. However, the motor flux linkage is not exactly known for a load torque observer. There is the problem of uncertainty to obtain very high precision position control. Therefore, a model reference adaptive observer is considered to overcome the problem of unknown parameter and torque disturbance in this paper. The system stability analysis is carried out using Lyapunov stability theorem. As a result, asymptotically stable observer gain can be obtained without affecting the overall system response. The load disturbance detected by the asymptotically stable adaptive observer is compensated by feedforwarding the equivalent current which gives fast response. The experimental results are presented in the paper using DSP TMS320c31.

• Earthquakes and Structures
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• 제22권3호
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• pp.231-243
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• 2022

Beam-column joints (BCJs) are recognized among the most crucial zones in reinforced concrete structures, as they are the critical elements subjected to a complex state of forces during a severe earthquake. Under such conditions, BCJs exhibit behaviors with impacts that extend to the whole structure and significantly influence its ductility and capability of dissipating energy. The focus of this paper is to investigate the effect of undamaged transverse beam (secondary beams) on the ductility of concrete BCJs reinforced with conventional steel and shape memory alloys bars using pushover analysis at tip of beam under different axial load levels at the column using a nonlinear finite element model in ABAQUS environment. A numerical model of a BCJ was constructed and the analysis outcomes were verified by comparing them to those obtained from previous experiments found in the literature. The comparison evidenced the capability of the calibrated model to predict the load capacity response of the joint. Results proved the ability of undamaged secondary beams to provide a noticeable improvement to the ductility of reinforced concrete joints, with a very negligible loss in load capacity. However, the effect of secondary beams can become less significant if the beams are damaged due to seismic effects. In addition, the axial load was found to significantly enhance the performance of BCJs, where the increase in axial load magnified the capacity of the joint. However, higher values of axial load resulted in greater initial stiffness of the BCJ.

• Steel and Composite Structures
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• 제46권6호
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• pp.731-744
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• 2023

Vehicle load information is an important role in operating and ensuring the structural health of cable-stayed bridges. In this regard, an efficient and economic method is proposed for vehicle load detection based on the observed cable tension and vehicle position using a graph neural network (GNN). Datasets are first generated using the practical advanced analysis program (PAAP), a robust program for modeling and considering both geometric and material nonlinearities of bridge structures subjected to vehicle load with low computational costs. With the superiority of GNN, the proposed model is demonstrated to precisely capture complex nonlinear correlations between the input features and vehicle load in the output. Four popular machine learning methods including artificial neural network (ANN), decision tree (DT), random forest (RF), and support vector machines (SVM) are refereed in a comparison. A case study of a cable-stayed bridge with the typical truck is considered to evaluate the model's performance. The results demonstrate that the GNN-based model provides high accuracy and efficiency in prediction with satisfactory correlation coefficients, efficient determination values, and very small errors; and is a novel approach for vehicle load detection with the input data of the existing monitoring system.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1987년도 춘계학술발표회 논문집
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• pp.52-55
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• 1987

In tihis paper an improved matching method using subtemplate of moving region and 3-step search algorithm is proposed It reduces heavy computational load of the conventional method. The proposed method is applied to an automatic target tracker using high speed 16 bit microprocessor in order to track one moving target in real time. Expericmental results show that the proposed method has better performance over the conventional methodin spite of greately reducing the computational load, even in came complex background.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1993년도 가을 학술발표회논문집
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• pp.131-138
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• 1993

To analysis machanical behavior for RC frame under monotonic & Cyclic load, it is needed to investigate elasto-plastic behavior for steel & concrete. Therefore, in this study, we idealized material model(steel and concrete) to take into account elasto-plastic, limit state, and developed structural analysis program that consider complex non-linearity. We investigated simple beam and portal frame under cyclic & monotonic loading, so we confirmed the propriety.

• 대한전자공학회논문지
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• 제24권4호
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• pp.684-695
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• 1987

In this paper, an improved matching method using subtemplate of moving region and 3-step search algorithm is proposed. It reduces heavy computational load of the conventional method and also can continuously track the target even with occlusion. The proposed method is applied to an automatic target tracker using high speed 16bit microprocessor in order to track one moving target in real time. Experimental results show that the proposed method has better performance over the conventional method in spite of greately reducing the computational load, even in case with complex background and/or with occlusion.

• Journal of Power Electronics
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• 제16권3호
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• pp.1036-1045
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• 2016

This paper presents a novel control strategy for passive output filter reduction using an active output filter. The proposed method achieves the dual-function of regulating the output voltage ripple and output voltage variation during load transients. The novel control strategy allows traditional simple voltage controllers to be used, without requiring the expensive current sensors and complex controllers used in conventional approaches. The proposed method is verified with results from a 125-W forward converter.

• 유기물자원화
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• 제30권1호
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• pp.41-47
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• 2022

본 연구는 강우시 산업단지에서 발생하는 비점오염원 유출 특성을 평가하여 비점오염원 부하량 및 원단위 산정을 위한 기초자료로 활용하기 위하여 C 산업단지에 대하여 강우유출수 수질모니터링을 수행하였다. 강우 사상별 유출량에 따른 EMC 산정 결과, 1차 강우시 BOD, COD_Mn, SS, T-N, T-P의 EMCs 범위는 각각 1.32~48.76, 3.32~43.75, 2.89~199.43, 2.76~8.93, 0.08~068 mg/L로 나타났으며, 2차 강우시는 각각 0.5~2.9, 2.71~7.13, 2.82~174.94, 1.33~4.03, 0.01~1.28 mg/L로 나타났다. 누적 유출량과 누적 오염부하량 비율 산정 결과, 강우 초기 유출량이 적은 시간에는 대부분 오염부하량이 강우 유출량보다 적지만 시간이 지남에 따라 강우 누적 유출량과 누적 오염부하량의 비가 1보다 커지면서 초기세척 현상이 일어났다.