• Land and Housing Review
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• v.15 no.2
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• pp.73-87
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• 2024

To evaluate the efficiency of commuting patterns, various commuting indicators such as excess commute and commuting potential utilized have been developed and used. It is crucial to calculate these indicators reasonably to reveal the differences in commuting patterns among metropolitan areas and to consider these in the process of formulating commuting policies. However, commuting indicators are generally calculated at the administrative district level, and thus, they are not free from the problem of the modifiable areal unit problem (MAUP). This issue can undermine the rationality of comparing commuting efficiency between metropolitan areas, making it necessary to handle the calculation of commuting indicators carefully. Therefore, this study utilises Monte Carlo Simulation to calculate optimal, actual, and maximum commuting distances, and thereby presents the excess commute and the commuting potential utilized. To apply Monte Carlo Simulation to the context of South Korea, a constrained Monte Carlo Simulation is conducted, where residential and workplace locations used in the simulation are selected based on the actual locations of buildings. The analysis is conducted on 13 metropolitan areas with established metropolitan plans using the 2016 Household Travel Survey data. The commuting indicators calculated through the simulation showed minimal differences compared to the results obtained through conventional methods. The comparison of commuting efficiency among metropolitan areas revealed that even if the degree of spafial balance between residential and workplace locations is similar, the actual commuting patterns can differ significantly. It is suggested that further research considering characteristics such as the area of each metropolitan region will be necessary in the future.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.350-356
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• 2005

A method of dynamic analysis of mechanical systems considering probabilistic properties is proposed in this paper. Probabilistic properties that result from manufacturing tolerances can be represented by means and standard deviations (or variances). The probabilistic characteristics of dynamic responses of constrained multi-body systems are obtained by two ways : the proposed analytical approach and the Monte Carlo simulation. The formerpaper, necessitates sensitivity information to calculate the standard deviations. In this a direct differentiation method is employed to find the sensitivities of constrained multi-body systems. To verify the accuracy of the proposed method, numerical examples are solved and the results obtained by using the proposed method are compared to those obtained by Monte Carlo simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1A
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• pp.73-79
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• 2002

In this paper, two interference suppression schemes (LCCMA, HIC) applied to the MC-CDMA system were proposed. The proposed schemes have advantages that it don't requires the other's spreading code and can be used even in mobile. The proposed HIC combines the proposed interference suppressor with PIC. Simulation is performed in various environments using the Monte Carlo method. Simulation results show that there is 1.4~3 times capacity increase in corresponding simulation environments. Also this scheme can take advantage of path diversity whereas the system using EGC, MRC, and PIC cannot. Therefore, as the number of path increase, a considerable performance improvement can be attained.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.3
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• pp.127-133
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• 2009

In this study, dimensionless-cumulative rainfall curves were generated by multivariate Monte Carlo method. For generation of rainfall curve rainfall storms were divided and made into dimensionless type since it was required to remove the spatial and temporal variances as well as differences in rainfall data. The dimensionless rainfall curves were divided into 4 types, and log-ratio method was introduced to overcome the limitations that elements of dimensionless-cumulative rainfall curve should always be more than zero and the sum total should be one. Orthogonal transformation by Johnson system and the constrained non-normal multivariate Monte Carlo simulation were introduced to analyse the rainfall characteristics. The generative technique in stochastic rainfall variation using multivariate Monte Carlo method will contribute to the design and evaluation of hydrosystems and can use the establishment of the flood disaster prevention system.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.73-77
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• 1986

Optimal input design problem for linear regression model with constrained output variance has been considered. It is shown that the optimal input signal for the linear regression model can also be realized as an ARMA process. Monte-Carlo simulation results show that the optimal stochastic input leads to comparatively better estimation accuracy than white input signal.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.453-463
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• 2013

The probabilistic nature of renewable energy, especially wind energy, increases the needs for new forms of planning and operating with electrical power. This paper presents a novel approach for determining the short-term generation schedule for optimal operations of wind energy-integrated power systems. The proposed probabilistic security-constrained optimal power flow (P-SCOPF) considers dispatch, network, and security constraints in pre- and post-contingency states. The method considers two sources of uncertainty: power demand and wind speed. The power demand is assumed to follow a normal distribution, while the correlated wind speed is modeled by the Weibull distribution. A Monte Carlo simulation is used to choose input variables of power demand and wind speed from their probability distribution functions. Then, P-SCOPF can be applied to the input variables. This approach was tested on a modified IEEE 30-bus system with two wind farms. The results show that the proposed approach provides information on power system economics, security, and environmental parameters to enable better decision-making by system operators.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1064-1072
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• 2017

The power of controlled generators in microgrids randomly fluctuate because of the stochastic volatility of the outputs of photovoltaic systems and wind turbines as well as the load demands. To address and dispatch these stochastic factors for daily operations, a dynamic economic dispatch model with the goal of minimizing the generation cost is established via chance-constrained programming. A Monte Carlo simulation combined with particle swarm optimization algorithm is employed to optimize the model. The simulation results show that both the objective function and constraint condition have been tightened and that the operation costs have increased. A higher stability of the system corresponds to the higher operation costs of controlled generators. These operation costs also increase along with the confidence levels for the objective function and constraints.

• Journal of The Geomorphological Association of Korea
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• v.26 no.4
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• pp.21-31
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• 2019

Timing of terrace formation is a key information for understanding the evolution of fluvial systems. In particular, dating strath terrace (i.e. timing of terrace abandonment) is more difficult than depositional terrace that is conventionally constrained by radiocarbon, OSL and other dating methods targeting samples within terrace deposit. Surface exposure dating utilizing cosmogenic ¹⁰Be provides more reliability because it can be applied directly to the surface of a fluvial terrace. Thus, this method has been increasingly used for alluvial deposits. As well as other geomorphic surfaces over the last decades. Some inherent conditions, however, such as post-depositional ¹⁰Be concentration (i.e. inheritance), surface erosion rate, and density change challenge the application of cosmogenic ¹⁰Be to depositional terrace surface against simple bedrock surface. Here we present the first application of ¹⁰Be depth profile dating to a thin-gravel covered strath terrace in Korea. Monte Carlo simulation (MCS) helped us in better constraining the timing of abandonment of the strath terrace, since which its surface stochastically denuded with time, causing unexpected change of ¹⁰Be production with depth. The age of the strath terrace estimated by MCS was 109 ka, ~4% older than the one (104 ka) calculated by simple depth profile dating, which yielded the best-fit surface erosion rate of 2.1 mm/ka. Our study demonstrates that the application of ¹⁰Be depth profile dating of strath terrace using MCS is more robust and reliable because it considers post-depositional change of initial conditions such as erosion rate.

• Structural Engineering and Mechanics
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• v.52 no.1
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• pp.149-172
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• 2014

Four algorithms for damage detection of trusses are presented in this paper. These approaches can detect damage by using both complete and incomplete measurements. The suggested methods are based on the minimization of the difference between the measured and analytical static responses of structures. A non-linear constrained optimization problem is established to estimate the severity and location of damage. To reach the responses, the successive quadratic method is used. Based on the objective function, the stiffness matrix of the truss should be estimated and inverted in the optimization procedure. The differences of the proposed techniques are rooted in the strategy utilized for inverting the stiffness matrix of the damaged structure. Additionally, for separating the probable damaged members, a new formulation is proposed. This scheme is employed prior to the outset of the optimization process. Furthermore, a new tactic is presented to select the appropriate load pattern. To investigate the robustness and efficiency of the authors' method, several numerical tests are performed. Moreover, Monte Carlo simulation is carried out to assess the effect of noisy measurements on the estimated parameters.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.49-56
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• 2013

In this paper, for constrained optimization problem, one multi-objective optimization algorithm that ensures both performance robustness and constraint feasibility is proposed when uncertainties are involved in design variables. In the proposed algorithm, the gradient index of objective function assisted by design sensitivity with the help of finite element method is applied to evaluate robustness; the reliability calculated by the sensitivity-assisted Monte Carlo simulation method is used to assess the feasibility of constraint function. As a demonstration, the performance and numerical efficiency of the proposed method is investigated through application to the optimal design of TEAM problem 22--a superconducting magnetic energy storage system.