• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.529-543
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• 2021

Inevitable source-uncertainties in geometry configuration, boundary condition, and material properties may deviate the structural dynamics from its expected responses. This paper aims to examine the influence of these uncertainties on the vibration of functionally graded beams. Finite element procedures are presented for Timoshenko beams and utilized to generate reliable datasets. A prerequisite to the uncertainty quantification of the beam vibration using Monte Carlo simulation is generating large datasets, that require executing the numerical procedure many times leading to high computational cost. Utilizing artificial neural networks to model beam vibration can be a good approach. Initially, the optimal network for each beam configuration can be determined based on numerical performance and probabilistic criteria. Instead of executing thousands of times of the finite element procedure in stochastic analysis, these optimal networks serve as good alternatives to which the convergence of the Monte Carlo simulation, and the sensitivity and probabilistic vibration characteristics of each beam exposed to randomness are investigated. The simple procedure presented here is efficient to quantify the uncertainty of different stochastic behaviors of composite structures.

• Journal of applied mathematics & informatics
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• v.42 no.2
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• pp.223-235
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• 2024

In this paper, our primary focus revolves around the examination of a set of fractional stochastic models. Through our investigation, we can establish the presence of a solution and its distinctiveness. Additionally, we employ a moment-based algorithm to estimate the coefficients within these models and provide evidence that these estimations maintain their asymptotic characteristics. To support this claim, we conduct experimental studies using simulations and numerical examples.

• Smart Structures and Systems
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• v.23 no.6
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• pp.641-651
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• 2019

The stochastic stability control of the parameter-excited vibration of an inclined stay cable with multiple modes coupling under random and periodic combined support disturbances is studied by using the direct eigenvalue analysis approach based on the response moment stability, Floquet theorem, Fourier series and matrix eigenvalue analysis. The differential equation with time-varying parameters for the transverse vibration of the inclined cable with control under random and deterministic support disturbances is derived and converted into the randomly and deterministically parameter-excited multi-degree-of-freedom vibration equations. As the stochastic stability of the parameter-excited vibration is mainly determined by the characteristics of perturbation moment, the differential equation with only deterministic parameters for the perturbation second moment is derived based on the $It{\hat{o}}$ stochastic differential rule. The stochastically and deterministically parameter-excited vibration stability is then determined by the deterministic parameter-varying response moment stability. Based on the Floquet theorem, expanding the periodic parameters of the perturbation moment equation and the periodic component of the characteristic perturbation moment expression into the Fourier series yields the eigenvalue equation which determines the perturbation moment behavior. Thus the stochastic stability of the parameter-excited cable vibration under the random and periodic combined support disturbances is determined directly by the matrix eigenvalues. The direct eigenvalue analysis approach is applicable to the stochastic stability of the control cable with multiple modes coupling under various periodic and/or random support disturbances. Numerical results illustrate that the multiple cable modes need to be considered for the stochastic stability of the parameter-excited cable vibration under the random and periodic support disturbances, and the increase of the control damping rather than control stiffness can greatly enhance the stochastic stability of the parameter-excited cable vibration including the frequency width increase of the periodic disturbance and the critical value increase of the random disturbance amplitude.

• Health Policy and Management
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• v.25 no.2
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• pp.97-106
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• 2015

Background & Methods: The purpose of this research is to estimate the efficiency of the pharmaceutical firms and the determinants of their efficiency. Stochastic frontier analysis(SFA) and panel study are applied to the data of 60 domestic pharmaceutical firms from 2006 to 2012. Results & Conclusion: First, the result of the stochastic frontier analysis shows that overall efficiency of the pharmaceutical firms is increasing as time goes by. However, if firms are classified by the scale, the larger firms show more efficiency and if classified by the degree of innovativeness, the innovative firms show more efficiency compared to the non-innovative firms. This evidences show that the scale and R&D investment have significant relationships with the efficiency of the pharmaceutical firms. Therefore, it is necessary to increase the national level of investment for the fundamental researches to vitalize R&D of the new drugs. Second, the result of estimation of the determinants of efficiency shows that the firms with larger sales promotion expenses and entertainment expenses have less efficiency compared to the other firms. This can be explained by the structural characteristics of the small generic pharmaceutical firms. Therefore, the government had better make the pharmaceutical firms to reduce sales promotion and entertainment expenses and increase R&D expenses by introducing systems such as global budgeting system on medicine or reference pricing system.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.270-279
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• 2000

This paper describes the on-chip learning algorithm of neural networks using the stochastic pulse arithmetic. Stochastic pulse arithmetic is the computation using the numbers represented by the probability of 1' and 0's occurrences in a random pulse stream. This stochastic arithmetic has the merits when applied to neural network ; reduction of the area of the implemented hardware and getting a global solution escaping from local minima by virtue of the stochastic characteristics. And in this study, the on-chip learning algorithm is derived from the backpropagation algorithm for effective hardware implementation. We simulate the nonlinear separation problem of the some character patterns to verify the proposed learning algorithm. We also had good results after applying this algorithm to recognize printed and handwritten numbers.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.38-49
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• 2012

In this study, we analyze statistical characteristics of influent water quality in Daejeon waste water treatment plant and apply a stochastic model for data generation. In the analysis, the influent water quality data from year 2003 to 2008, except for year 2006, are used. Among water quality variables, we find strong correlations between BOD and T-N; T-N and T-P; BOD and T-P; $COD_{Mn}$ and T-P; and BOD and $COD_{Mn}$. We also find that different water quality variables follow different theoretical probability distribution functions, which also depends on whether the seasonal cycle is removed. Finally, we generate the influent water quality data using the multi-season 1st Markov model (Thomas-Fiering model). With model parameters calibrated for the period 2003~2005, the generated data for 2007~2008 are well compared with observed data showing good agreement in general. BOD and T-N are underestimated by the stochastic model. This is mainly due to the statistical difference in observed data itself between two periods of 2003~2005 and 2007~2008. Therefore, we expect the stochastic model can be applied with more confidence in the case that the data follows stationary pattern.

• Wind and Structures
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• v.27 no.6
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• pp.399-416
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• 2018

In order to reveal the independent relationship between track irregularity and wind loads, the stochastic characteristics of train-bridge coupling systems subjected to wind loads were investigated by the multi-sample calculation. The vehicle was selected as 23 degrees of freedom dynamical model, and the bridge was described by three-dimensional finite element model. It was assumed that the wind loads were random processes with strong spatial correlation, while the track irregularities were stationary random ones. As a case study, a high-speed train running on a cable-stayed bridge subjected to wind loads was studied. The effect of rail irregularities was deemed to be independent of the effect of wind excitations on the coupling system in the same wind circumstance for the same project, leading to the conclusion that the effect of wind loads and moving vehicle could be calculated separately. The variance results of the stochastic responses of vehicle-bridge coupling system under the action of wind loads and rail irregularities together were equivalent to the sum of the variance of the responses induced by each excitation. Therefore, when one of the input excitations is different, only the effect of changed loads needs to be assessed. Moreover, the new calculated results were combined with the effect of unchanged loads to present the stochastic response of coupling system subjected to the different excitations, reducing the cost of computations. The stochastic characteristics, the CFD (cumulative distribution function) of the coupling system with different wind velocities, vehicle speed, and vehicle marshalling were studied likewise.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.444-446
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• 2021

MANETs(Mobile Ad-hoc Networks) are composed of mobile nodes that are not subordinate to fixed networks and have the feature that can form their own networks. they are used in various fields for specific goals. The mobility model in MANET can be applied in various ways depending on the purpose of usage. The random mobility model has the advantage of being simple and easy to implement, so it is being used the most. In a MANET, it is assumed that each node moves independently. The random movement model is a good model for expressing this independence of each node. However, it is insufficient to express the characteristics of all nodes with only random properties of individual nodes. This paper limits the stochastic mobility model applicable in MANET. we compare the proposed stochastic mobility model and the random mobility model. We confirm that the proposed mobility model is applied to the routing protocol to show improved characteristics in terms of energy consumption efficiency.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.213-231
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• 2003

This paper uses the Efficient Method of Moments(EMM) of Gallant and Tauchen to estimate continuous-time stochastic volatility diffusion model for the Korean Composite Stock Price Index, sampled daily over $1995\sim2002$. The estimates display non-normality of stock index return, leptokurtic distribution, and stochastic volatility. Funker, this study suggests that two factor stochastic volatility model will be more desirable than one factor stochastic volatility model to estimate daily Korean stock return and also suggests that the stochastic volatility diffusions should allow for Poisson jumps of time-varying intensity.

• Structural Engineering and Mechanics
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• v.53 no.2
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• pp.297-309
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• 2015

The purpose of this work is to analyze the effect of structure parameter disturbance on the dynamic characteristics of a hydropower station powerhouse. A vibration model with a head-cover system is established, and then the general disturbance problem analysis methods are discussed. Two new formulae based on two types of disturbances are developed from existing methods. The correctness and feasibility of these two formulae are validated by analyzing the hydropower station powerhouse vibration model. The appropriate calculation method for disturbance of the hydropower station powerhouse vibration dynamic characteristics is derived.