• Coupled systems mechanics
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• v.2 no.2
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• pp.159-174
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• 2013

The present work aims at investigating the nonlinear dynamics, bifurcations, and stability of an axially accelerating beam with an intermediate spring-support. The problem of a parametrically excited system is addressed for the gyroscopic system. A geometric nonlinearity due to mid-plane stretching is considered and Hamilton's principle is employed to derive the nonlinear equation of motion. The equation is then reduced into a set of nonlinear ordinary differential equations with coupled terms via Galerkin's method. For the system in the sub-critical speed regime, the pseudo-arclength continuation technique is employed to plot the frequency-response curves. The results are presented for the system with and without a three-to-one internal resonance between the first two transverse modes. Also, the global dynamics of the system is investigated using direct time integration of the discretized equations. The mean axial speed and the amplitude of speed variations are varied as the bifurcation parameters and the bifurcation diagrams of Poincare maps are constructed.

• Journal of the Chungcheong Mathematical Society
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• v.29 no.4
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• pp.631-642
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• 2016

This article deals with one-dimension backward heat conduction problem (BHCP). A new approach based on least squares support vector machines (LS-SVM) is proposed for obtaining their approximate solutions. The approximate solution is presented in closed form by means of LS-SVM, whose parameters are adjusted to minimize an appropriate error function. The approximate solution consists of two parts. The first part is a known function that satisfies initial and boundary conditions. The other is a product of two terms. One term is known function which has zero boundary and initial conditions, another term is unknown which is related to kernel functions. This method has been successfully tested on practical examples and has yielded higher accuracy and stable solutions.

• Journal of the Korean Society of Safety
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• v.32 no.1
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• pp.115-120
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• 2017

The aim of this study is to develop construction safety and health management cost prediction model using support vector machine (SVM). To this end, theoretical concept of SVM is investigated to formulate the cost prediction model. Input and output variables have been selected by analyzing the balancing accounts for the completed construction project. In order to train and validate the proposed prediction model, 150 data sets have been gathered from field. Effects of SVM parameters on prediction accuracy are analyzed and from which the optimal parameter values have been determined. The prediction performance tests are conducted to confirm the applicability of the proposed model. Based on the results, it is concluded that the proposed SVM model can effectively be used to predict the construction safety and health management cost.

• Journal of the Korean Society for Advanced Composite Structures
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• v.6 no.1
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• pp.45-50
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• 2015

This study performed a finite element crash analysis of support structures made of various composite materials for road facilities. The effects of different material properties of composites for various parameters are studied using the finite element commercial package for this study. In this study, the existing finite element analysis of composite post structures using the LS-DYNA program is further extended to compare dynamic behaviors against car crash of the structures made of various composite materials. The several numerical examples show the comparison of the nonlinear dynamic effects for different materials.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.155-163
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• 2005

This paper applies Support Vector Regression (SVR) to estimate and forecast nonlinear autoregressive integrated (ARI) model of the daily exchange rates of four currencies (Swiss Francs, Indian Rupees, South Korean Won and Philippines Pesos) against U.S. dollar. The forecasting abilities of SVR are compared with linear ARI model which is estimated by OLS. Sensitivity of SVR results are also examined to kernel type and other free parameters. Empirical findings are in favor of SVR. SVR method forecasts exchange rate level better than linear ARI model and also has superior ability in forecasting the exchange rates direction in short test phase but has similar performance with OLS when forecasting the turning points in long test phase.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.2
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• pp.114-126
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• 2009

In this paper, a versatile multi-criteria optimization concept for fatigue life prediction is introduced. Multi-criteria decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

• IE interfaces
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• v.25 no.3
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• pp.338-346
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• 2012

Regarding the green environment, it is important to boost the spread of environmentally friendly vending machines and to operate the vehicles for their inventory replenishments while minimizing emissions of greenhouse gases. In general, the vending machine management company lacks capability to operate the supply chain effectively in an integrated way under the dynamic, complex, and stochastic environment. This paper presents a decision support system, termed DSSVM, for the operations of the general and smart vending machine supply chains with stock-out-based, one stage item substitution in a green logistics environment. The DSSVM supports the estimation of item demand and substitution probabilities, determination of operation parameters, supply chain analysis, what-if analysis, and $CO_2$ analysis for which various analytical models are employed.

• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.83-93
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• 2007

This paper gives an attempt to build a decision support tool linked with a simulation software called ARENA for evaluating and comparing the performance of the push and pull material driven strategies operating in the flow shop environment with a bottleneck resource as the shop's constraint. To be fair for such evaluation, the comparison must be made fairly under the optimal setting of both systems' operating parameters. In this study, an optimal-seeking heuristic algorithm, Genetic Algorithm (GA), is employed to suggest a systems' best design based on the economic consideration, which is the profit generated from the system. Results from the study have revealed interesting outcomes, letting us know the strength and weakness of the push and pull mechanisms as well as the effect of each operating parameter to the overall system's financial performance.

• Proceedings of the KSRS Conference
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• v.1
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• pp.114-117
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• 2006

One of the most important tasks of ocean color observations is to determine the distribution of phytoplankton primary production. A variety of bio-optical algorithms have been developed estimate primary production from these parameters. In this communication, we investigated the possibility of using a novel universal approximator-support vector machines (SVMs)-as the nonlinear transfer function between oceanic primary production and the information that can be directly retrieved from satellite data. The VGPM (Vertically Generalized Production Model) dataset was used to evaluate the proposed approach. The PPARR2 (Primary Production Algorithm Round Robin 2) dataset was used to further compare the precision between the VGPM model and the SVM model. Using this SVM model to calculate the global ocean primary production, the result is 45.5 PgC $yr^{-1}$, which is a little higher than the VGPM result.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.990-993
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• 2005

This paper presents new results on designing a robust adaptive direct controller for a class of non-linear first order systems. The designing method based on the use of dead zone in the parameters' update law. It is shown that the size of the dead zone does not depend on the upper bounds of the disturbances. That means that even if the bounds are large, the tracking error will always converge to a set of the dead zone size. However, in the ideal case, when the exogenous signal functions and the function represents un-modeled dynamics of the systems equal to zero, the proposed controller does nt mean the convergence to zero of the tracking error. Computer simulation results show the effectiveness of the controller in dealing with the stated problems.