• Steel and Composite Structures
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• v.34 no.1
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• pp.155-170
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• 2020

Different parameters potentially affect the properties of corroded reinforced concrete beams. However, the high number of these parameters and their dependence cause that the effectiveness of the parameters could not be simply identified. In this study, an adaptive neuro-fuzzy inference system (ANFIS) was employed to determine the most influencing parameters on the properties of the corrosion-damaged reinforced concrete beams. 207 ANFIS models were developed to analyze the collected data from 107 reinforced concrete (RC) beams. The impact of 23 input parameters on nine output factors was investigated. The results of the paper showed the order of influence of each input parameter on the outputs and revealed that the input parameters regarding the uncorroded properties of concrete beams are the most influencing factors on the corresponding corroded properties of the beams.

• Journal of electromagnetic engineering and science
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• v.1 no.2
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• pp.139-145
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• 2001

In this paper, a coaxial sample holder is proposed with its de-embedding and parameter extraction procedure. The S-parameters were measured up to 1 GHz using network analyzer, HP8753D, and N-type connector together with the de-embedding of N-type connector. The proposed de-embedding procedure is performed to extract electrical parameters of blood glucose, which gives the permittivity of blood glucose. We also analyzed the error of extracted parameters, which are caused by instrument error and geometrical error. Using these error analyses, we reduced the error factors of extracted parameters. We extracted electrical parameters of glucose samples through these all extraction procedure and confirmed the possibility of glucose diagnosis system based on microwave system.

• Structural Engineering and Mechanics
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• v.50 no.5
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• pp.697-708
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• 2014

The intentional buckling design of micro-films has various potential applications in engineering. The buckling amplitude and critical strain of micro-films are the crucial parameters for the buckling design. In the reported studies, the film parameters were regarded as deterministic. However, the geometrical and physical parameters uncertainty of micro-films due to manufacturing becomes prominent and needs to be considered. In the present paper, the probabilistic nonlinear buckling analysis of micro-films with uncertain parameters is proposed for design accuracy and reliability. The nonlinear differential equation and its asymptotic solution for the buckling micro-film with nominal parameters are firstly established. The mean values, standard deviations and variation coefficients of the buckling amplitude and critical strain are calculated by using the probability densities of uncertain parameters such as the film span length, thickness, elastic modulus and compressive force, to reveal the effects of the film parameter uncertainty on the buckling deformation. The results obtained illustrate the probabilistic relation between buckling deformation and uncertain parameters, and are useful for accurate and reliable buckling design in terms of probability.

• Structural Engineering and Mechanics
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• v.84 no.1
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• pp.1-16
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• 2022

An efficient and accurate classification method for failure modes of reinforced concrete (RC) columns was proposed based on key characteristic parameters. The weight coefficients of seven characteristic parameters for failure modes of RC columns were determined first based on the support vector machine-recursive feature elimination. Then key characteristic parameters for classifying flexure, flexure-shear and shear failure modes of RC columns were selected respectively. Subsequently, a support vector machine with key characteristic parameters (SVM-K) was proposed to classify three types of failure modes of RC columns. The optimal parameters of SVM-K were determined by using the ten-fold cross-validation and the grid-search algorithm based on 270 sets of available experimental data. Results indicate that the proposed SVM-K has high overall accuracy, recall and precision (e.g., accuracy>95%, recall>90%, precision>90%), which means that the proposed SVM-K has superior performance for classification of failure modes of RC columns. Based on the selected key characteristic parameters for different types of failure modes of RC columns, the accuracy of SVM-K is improved and the decision function of SVM-K is simplified by reducing the dimensions and number of support vectors.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.969-972
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• 2005

This paper presents a GA-fuzzy $P^2ID$ control system for the flexible-joint robot arm. This controller is designed based on the parameter adjustment using fuzzy logic and genetic algorithms. According to the simulations, the better performance has been achieved acquired that the robot moved smoothly and met its required objectives. The results of comparison between 8 parameters and 10 parameters can be conclusion that the 10 parameters have setting time little than 8 parameters. In usability can be use 8 or 10 parameters these one.

• Structural Engineering and Mechanics
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• v.7 no.4
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• pp.387-400
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• 1999

Damage detection in civil engineering structures using the change in dynamic system parameters has gained a lot of scientific interest during the last decade. By repeating a dynamic test on a structure after a certain time of use, the change in modal parameters can be used to quantify and qualify damages. To be able to use the modal parameters confidentially for damage evaluation, the effect of other parameters such as excitation type, ambient conditions,... should be considered. In this paper, the influence of excitation type on the dynamic system parameters of a highway prestressed concrete bridge is investigated. The bridge, B13, lies between the villages Vilvoorde and Melsbroek and crosses the highway E19 between Brussels and Antwerpen in Belgium. A drop weight and ambient vibration are used to excite the bridge and the response at selected points is recorded. A finite element model is constructed to support and verify the dynamic measurements. It is found that the difference between the natural frequencies measured using impact weight and ambient vibration is in general less than 1%.

• International Journal of Automotive Technology
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• v.7 no.7
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• pp.859-866
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• 2006

This study employed the perturbation method, the Edgeworth series, the reliability optimization, the reliability sensitivity technique and the robust design to present a practical and effective approach for the robust reliability design of vehicle components with arbitrary distribution parameters on the condition of known first four moments of original random variables. The theoretical formulae of the robust reliability design for vehicle components with arbitrary distribution parameters are obtained. The reliability sensitivity is added to the reliability optimization design model and the robust reliability design is described as a multi-objection optimization. On the condition of known first four moments of original random variables, the respective program can be used to obtain the robust reliability design parameters of vehicle components with arbitrary distribution parameters accurately and quickly.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.179-184
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• 2005

Shear strength parameters obtained from filed survey are important factors in the analysis of slope stability. In this study, sensitivity analysis was performed to evaluate the effect of input parameters on the analysis of slope stability. The input parameters selected for sensitivity analysis were slope angle, cohesion, and friction angle. Monte-Carlo Simulation method was used for calculating input parameters and the factor of safety was computed by means of limit equilibrium method. A rock slope, which has failed in the field, was used for the sensitivity analysis in the analysis of slope stability. The result of analysis shows that the factor of safety of the rock slope was a little low. From partial correlation coefficient(PPC) of input parameters determined from the sensitivity analysis, slope stability was dependant on cohesion and slope angle. The effect of friction angle was lower than that of cohesion and slope angle on slope stability.

• Smart Structures and Systems
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• v.29 no.5
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• pp.729-746
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• 2022

In this paper, a nonlinear structural model updating methodology based on the Deep Belief Network (DBN) is proposed. Firstly, the instantaneous parameters of the vibration responses are obtained by the discrete analytical mode decomposition (DAMD) method and the Hilbert transform (HT). The instantaneous parameters are regarded as the independent variables, and the nonlinear model parameters are considered as the dependent variables. Then the DBN is utilized for approximating the nonlinear mapping relationship between them. At last, the instantaneous parameters of the measured vibration responses are fed into the well-trained DBN. Owing to the strong learning and generalization abilities of the DBN, the updated nonlinear model parameters can be directly estimated. Two nonlinear shear-type structure models under two types of excitation and various noise levels are adopted as numerical simulations to validate the effectiveness of the proposed approach. The nonlinear properties of the structure model are simulated via the hysteretic parameters of a Bouc-Wen model and a Giuffré-Menegotto-Pinto model, respectively. Besides, the proposed approach is verified by a three-story shear-type frame with a piezoelectric friction damper (PFD). Simulated and experimental results suggest that the nonlinear model updating approach has high computational efficiency and precision.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.410-419
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• 2018

Purpose: CLIMEX, a species distribution modeling tool, includes various types of parameters representing climatic conditions; the estimation of these parameters directly determines the model accuracy. In this study, we investigated the sensitivity of parameters for the climatic suitability calculated by CLIMEX for Metcalfa pruinosa in South Korea. Methods: We first changed 12 parameters and identified the three significant parameters that considerably affected the CLIMEX simulation response. Results: The result indicated that the simulation was highly sensitive to changes in lower optimal temperatures, lower soil moisture thresholds, and cold stress accumulation rate based on the sensitivity index, suggesting that these were the fundamental parameters to be used for fitting the simulation into the actual distribution. Conclusion: Sensitivity analysis is effective for estimating parameter values, and selecting the most important parameters for improving model accuracy.