• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.65-76
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• 2013

Traffic accidents at signalized intersections have been increased annually so that it is required to examine the causation to reduce the accidents. However, the current existing accident models were developed mainly by using non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal the complicated causation for traffic accidents, though they are the right choice to study randomness and non-linearity of accidents. Therefore, it is required to utilize another statistical method to make up for the lack of the non-linear regression methods. This study developed accident prediction models for 4 legged signalized intersections with Poisson methods and compared them with structural equation models. This study used structural equation methods to reveal the complicated causation of traffic accidents, because the structural equation method has merits to explain more causational factors for accidents than others.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.10
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• pp.24-31
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• 2006

In this paper, mechanical behavior of unidirectional composites with flexible matrix was predicted by geometrical non-linear finite element analysis. Two typical idealized unit cells of square and hexagonal fiber arrays were modeled and these were subjected to different loadings. The stress-strain behavior of composites was predicted from which the effective properties were calculated. The hyperelasticity of polyurethane matrix was considered using Mooney-Rivlin model. In result, the stress-strain behavior of flexible composites shows non-linearity, especially it is remarkable under transverse normal and shear loading conditions. In this cases, there are great difference between square and hexagonal fiber array models.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.563-568
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• 2007

This paper presents a methodology for predicting nonlinear time series based on the neural network with weighted fuzzy membership functions (NEWFM). The degree of classification intensity is obtained by bounded sum of weighted fuzzy membership functions extracted by NEWFM, then weighted average defuzzification is used for predicting nonlinear time series. The experimental results demonstrate that NEWFM has the classification capability of 92.22% against the target class of GDP. The time series created by NEWFM model has a relatively close approximation to the GDP which is a typical business cycle indicator, and has been proved to be a useful indicator which has the turning point forecasting capability of average 12 months in the peak point and average 6 months in the trough point during 5th to 8th cyclical period. In addition, NEWFM measures the efficiency of the economic indexes by the feature selection and enables the users to forecast with reduced numbers of 7 among 10 leading indexes while improving the classification rate from 90% to 92.22%.

• Journal of Environmental Policy
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• v.13 no.2
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• pp.21-38
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• 2014

In response to global warming, the effect of the air temperature on water temperature has been noticed. The change in water temperature in river environment results in the change in water quality and ecosystem, especially Dissolved Oxygen (DO) level, and shifts in aquatic biota. Efforts need to be made to predict future water temperature in order to understand the timing of the projected river temperature. To do this, the data collected by the Ministry of Environment and the Korea Meteororlogical Administration has been used to build a nonlinear relationship between air and water temperature. The logistic function that includes four different parameters was selected as a working model and the parameters were optimized using SCE algorithm. Weekly average values were used to remove time scaling effect because the time scale affects maximum and minimum temperature and then river environment. Generally speaking nonlinear logistic model shows better performance in NSC and RMSE and nonlinear logistic function is recommendable to build a relationship between air and water temperature in Korea. The results will contribute to determine the future policy regarding water quality and ecosystem for the decision-driving organization.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.6
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• pp.130-137
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• 2018

Many constitutive models for concrete have been developed to predict the nonlinear behavior of concrete members considerably. The constitutive model for reinforcing bar that include the tension stiffening effect due to the bond characteristics between steel bars and concrete is being studied but the bilinear model is generally used. It was found that the buckling of the longitudinal reinforcing bars is controlled the nonlinear behavior of hybrid precast concrete panel, which is being developed for core wall. In this study, the constitutive models that can consider the embedding and buckling effects of reinforcing bar are investigated and a new model combing these constitutive models is proposed. In order to verify the proposed model, the analysis results are compared with experimental results of the concrete wall and hybrid precast concrete panel. The analysis of embedding-effect-only modeling predicted that the deformation increases continually without the decrease in the load carrying capacity. However, the analysis results of proposed model showed good agreement with some experimental results, thus verifying the proposed computational model.

• The Journal of the Acoustical Society of Korea
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• v.27 no.6
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• pp.309-318
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• 2008

In this paper, we discuss a method for efficiently coding the high-band signal in the split-band coding approach where an input signal is divided into two bands and then each band may be encoded separately. Generally, and especially through the research on the artificial bandwidth extension (BWE), it is well known that there is a correlation between the two bands to some degree. Therefore, some coding gain could be achieved by utilizing the correlation. In the BWE-prediction-based coding approach, using a simple linear BWE function may not yield optimal results because the correlation has a non-linear characteristic. In this paper, we investigate the new coding scheme more in details. A few representative BWE functions including linear and non-linear ones are investigated and compared to find a suitable one for the coding purpose. In addition, it is also discussed whether there are some additional gains in combining the BWE coder with the predictive vector quantizer which exploits the temporal correlation.

• Composites Research
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• v.19 no.3
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• pp.29-36
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• 2006

Since composite materials have anisotropic properties that depend on their stacking angle and sequence, the analysis of joints with isotropic adherends is limited in describing the behavior of the adhesive Joint with composite adherends. In this study, the nonlinear solution for adhesive joints with composite adherends was derived by incorporating the nonlinear behavior of the adhesive into the analysis. The behavior of the laminated composite tube was first analyzed, and the stress distributions of the composite tubular adhesive joint were calculated by including the nonlinear properties of the adhesive. The effect of the stacking sequence of composite adherends and bonding length on torque capacities of joints was examined, and results of the nonlinear analysis were also compared with those of the linear analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.559-564
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• 2010

The GMDH(Group Method of Data Handling) algorithm can be used to predict the complex nonlinear systems. The traditional GMDH algorithm produces the prdicted output of the system model in the output layer through the input layer and the intermediate layers as the prescribed process. The outputs of each layer are produced only by the outputs of the former layer. However, in the traditional GMDH algorithm, though the optimal structure of each layer is derived, the overall structure may not be derived optimally. To overcome this problem, GMDH prediction model which has the overall optimal structure is constructed by feeding back the error between the predicted output and the real output. This can make the prediction more precise. The capability improvement of the proposed algorithm compared to the traditional algorithm is verified through computer simulation.

• Journal of the Korean Geotechnical Society
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• v.38 no.12
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• pp.103-112
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• 2022

The existing subsidence prediction method based on the measurement data were confirmed in this study through literature research. It was confirmed that the hyperbolic method and the Asaoka method showed high accuracy, while the other prediction methods showed significantly low accuracy. Based on the analysis results, the limitations of the existing prediction equations were derived, and the improvement method of the settlement prediction equations was suggested. In this study, a weighted nonlinear regression analysis method that gives higher weight to the later data was proposed to improve the existing hyperbolic method.

• Journal of the Earthquake Engineering Society of Korea
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• v.1 no.1
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• pp.1-10
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• 1997

Current seismic design philosophy for reinforced concrete (RC) structures on energy dissipation through large inelastic defomations. A nonlinear dynamic analysis which is used to represent this behavior is time consuming and expensive, particularly if the computations have to be repeated many times. Therefore, the selection of an efficient yet accurate alogorithm becomes important. The main objective of the present study is to propose a new technique herein called the prediction approach with siffness measure (PASM) method in the convetional direct integration methods, the triangular decomposition of matrix is required for solving equations of motion in every time step or every iteration. The PASM method uses a limited number of predetermined decomposed effective matrices obtained from stiffness states of the structure when it is deformed into the nonlinear range by statically applied cyclic loading. The method to be developed herein will reduce the overall numerical effort when compared to approaches which recompute the stiffness in each time step or iteration.