• Journal of the Korean Mathematical Society
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• v.59 no.6
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• pp.1153-1170
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• 2022

In this paper, we investigate the portfolio optimization problem under the SVCEV model, which is a hybrid model of constant elasticity of variance (CEV) and stochastic volatility, by taking into account of minimum-entropy robustness. The Hamilton-Jacobi-Bellman (HJB) equation is derived and the first two orders of optimal strategies are obtained by utilizing an asymptotic approximation approach. We also derive the first two orders of practical optimal strategies by knowing that the underlying Ornstein-Uhlenbeck process is not observable. Finally, we conduct numerical experiments and sensitivity analysis on the leading optimal strategy and the first correction term with respect to various values of the model parameters.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.167.4-167
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• 2001

Accurate mathematical models of spacecraft components are an essential of spacecraft attitude control system design, analysis and simulation. Gyro is one of the most important spacecraft components used for attitude propagation and control. Gyro errors may seriously degrade the accuracy of the calculated spacecraft angular rate and of attitude estimates due to inherent drift and bias errors. In this paper, a detailed mathematical model of gyro containing the relationships for predicting spacecraft angular rate and disturbances is proposed. Stochastic model describing random drift behavior is discussed in frequency domain and time domain. In order to illustrate this approach, we analyze the behavior for Litton´s Space Inertial Reference Uint(SIRU).

• International conference on construction engineering and project management
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• 2015.10a
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• pp.169-173
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• 2015

The linear scheduling method or line-of-balance (LOB) is a popular choice for projects that involve repetitive tasks during project execution. The method, however, produces deterministic schedule that does not convey a range of potential project outcomes under uncertainty. This results from the fact the basic scheduling parameters such as crew production rates are estimated to be deterministic based on single-point value inputs. The current linear scheduling technique, therefore, lacks the capability of reflecting the fluctuating nature of the project operation. In this paper the authors address the issue of how the variability of operation and production rates affects schedule outcomes and show a more realistic description of what might be a realistic picture of typical projects. The authors provide a solution by providing a more effective and comprehensive way of incorporating the crew performance variability using a Monte Carlo simulation technique. The simulation outcomes are discussed in terms of how this stochastic approach can overcome the shortcomings of the conventional linear scheduling technique and provide optimum schedule solutions.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.254-255
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• 2023

This paper discovers a robust managerial strategy for a stochastic inventory of perishable products, where the model experiences changing factors including inner parameters and an external disturbance with unknown form. An analytical solution for the optimization problem can be obtained by applying the Hamilton-Bellman-Jacobi equation, however the policy result cannot completely suppress the oscillation from the external disturbance. Therefore, an intelligent approach named Radial Basis Function Neural Networks is applied to estimate the unknown disturbance and provide a robust controller to manipulate the inventory level more effective. The final results show the outstanding performance of RBFNN controller, where both the estimation error and control error are guaranteed in the predefined limit.

• Water for future
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• v.28 no.2
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• pp.169-180
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• 1995

The cost of a looped pipe network is affected by a set of loop flows. The mathematical model for optimizing the looped pipe network is expressed in the optimal set of loop flows to apply to a stochastic optimization method. Because the feasible region of the looped pipe network problem is nonconvex with multiple local optima, the Modified Stochastic Probing Method is suggested to efficiently search the feasible region. The method consists of two phase: i) a global search phase(the stochastic probing method) and ii) a local search phase(the nearest neighbor method). While the global search sequentially improves a local minimum, the local search escapes out of a local minimum trapped in the global search phase and also refines a final solution. In order to test the method, a standard test problem from the literature is considered for the optimal design of the paralled expansion of an existing network. The optimal solutions thus found have significantly smaller costs than the ones reported previously by other researchers.

• Korea journal of population studies
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• v.33 no.1
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• pp.161-189
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• 2010

Dealing with uncertainty has been a critical issue in demographic and population forecasting since 1980. This study reviews methodological developments in demographic and population forecasting over the last several decades. First, this study reviews the important issue of the uncertainty surrounding demographic forecasts. Several limitations of the traditional scenario approach to dealing with uncertainty are also discussed. Second, in forecasting demographic processes such as mortality, fertility, and migration, three approaches of stochastic forecasting are identified and discussed: expert judgment, statistical modeling, and analysis of historical forecast errors. Finally, this study discusses the current issues and directions for future research in stochastic demographic forecasting.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.2
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• pp.138-148
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• 2012

A stochastic reliability analysis model has been developed for evaluating the time-dependent stability performance of armor units of rubble-mound breakwaters subjected to the multiple loads of arbitrary magnitudes which could be occurred randomly. The initial structural capacities and the damage rates of armor units of rubble-mound breakwaters could be estimated as a function of the incident wave height with a given return period by using the modified Hudson's formula and Melby's formula. The structural stability performances of armor units of rubble-mound breakwaters could be analyzed in detail through the lifetime reliability investigations according to the limit states such as the serviceability or ultimate limit state and the conditions of multiple loads. Finally, repair intervals for the structural management of armor units of rubble-mound breakwaters could quantitatively be evaluated by a new approach suggested in this paper that has been based on the target probability for repair and the accumulated probabilities of failure obtained from the present stochastic reliability analysis model.

• Smart Structures and Systems
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• v.18 no.3
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• pp.569-584
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• 2016

This paper presents a method for stochastic modelling of fatigue crack growth and optimising inspection and maintenance strategy for the structural members of steel bridges. The fatigue crack evolution is considered as a stochastic process with uncertainties, and the Gamma process is adopted to simulate the propagation of fatigue crack in steel bridge members. From the stochastic modelling for fatigue crack growth, the probability of failure caused by fatigue is predicted over the service life of steel bridge members. The remaining fatigue life of steel bridge members is determined by comparing the fatigue crack length with its predetermined threshold. Furthermore, the probability of detection is adopted to consider the uncertainties in detecting fatigue crack by using existing damage detection techniques. A multi-objective optimisation problem is proposed and solved by a genetic algorithm to determine the optimised inspection and maintenance strategy for the fatigue affected steel bridge members. The optimised strategy is achieved by minimizing the life-cycle cost, including the inspection, maintenance and failure costs, and maximizing the service life after necessary intervention. The number of intervention during the service life is also taken into account to investigate the relationship between the service life and the cost for maintenance. The results from numerical examples show that the proposed method can provide a useful approach for cost-effective inspection and maintenance strategy for fatigue affected steel bridges.

• Environmental and Resource Economics Review
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• v.30 no.4
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• pp.581-605
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• 2021

The purpose of this study is to provide basic data for improving energy efficiency by estimating the regional energy efficiency in Korea using the stochastic frontier approach beyond the energy intensity that has been traditionally used as an indicator of energy efficiency. In this paper, energy efficiency and energy intensity efficiency were estimated as a stochastic distance function from 1998 to 2018 for 16 cities and provinces in Korea. In addition, the robustness of energy efficiency according to the capital stock estimation methods which had been mixed in previous studies was reviewed. As a result of the analysis, there is a significant change in regional rankings according to the three energy efficiency indicators, so they should be used complementary to each other. Second, while the energy efficiency improved little by little over time, the energy intensity efficiency decreased slightly though. Lastly, energy efficiency by region according to the capital stock estimation method was not robust. Care must be taken in estimating capital stock, which is important in economic analysis.

• Journal of Ocean Engineering and Technology
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• v.33 no.3
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• pp.222-228
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• 2019

An extreme value analysis (EVA) is essential to obtain a design value for highly nonlinear variables such as long-term environmental data for wind and waves, and slamming or sloshing impact pressures. According to the extreme value theory (EVT), the extreme value distribution is derived by multiplying the initial cumulative distribution functions for independent and identically distributed (IID) random variables. However, in the position mooring of DNVGL, the sampled global maxima of the mooring line tension are assumed to be IID stochastic variables without checking their independence. The ITTC Recommended Procedures and Guidelines for Sloshing Model Tests never deal with the independence of the sampling data. Hence, a design value estimated without the IID check would be under- or over-estimated because of considering observations far away from a Weibull or generalized Pareto distribution (GPD) as outliers. In this study, the IID sampling data are first checked in an EVA. With no IID random variables, an automatic resampling scheme is recommended using the block maxima approach for a generalized extreme value (GEV) distribution and peaks-over-threshold (POT) approach for a GPD. A partial autocorrelation function (PACF) is used to check the IID variables. In this study, only one 5 h sample of sloshing test results was used for a feasibility study of the resampling IID variables approach. Based on this study, the resampling IID variables may reduce the number of outliers, and the statistically more appropriate design value could be achieved with independent samples.