• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.130-134
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• 2007

Classical full waveform inversion for velocity estimation defines the objective function as the $l^2$ -norm of differences between the modeled and the observed wavefields. Although widely used, the results of this method have been less than satisfactory. A moderate improvement of this method is to define the objective function as the $l^2$ -norm of differences between the logarithms of the modeled and observed wavefields. In this paper we propose new objective functions of waveform inversion. They produce better results in sub-salt imaging than those of the classical and the logarithmic objective functions. One objective function defines the residual as the difference between $L^{th}$ power of the modeled wavefields and that of the observed wavefields. Another defines the residual as the difference between the integral of the $L^{th}$ power of the modeled wavefields and that of the observed wavefields. We apply these new objective functions to the synthetic SEG/EAGE salt model, and show that our new waveform inversion algorithms provide more accurate results than those of the classical and logarithmic waveform inversion methods.

• Journal of dental hygiene science
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• v.19 no.3
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• pp.147-153
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• 2019

Background: With increased interest in oral health, several efforts have been made to improve oral health conditions. To achieve this, needs for oral health must be precisely determined and accurately measured. Therefore, factors influencing both objective unmet dental needs, which were determined by experts, and perceived unmet dental needs, which were determined by patients, were examined in this study. Methods: Responses of 17,735 respondents aged greater than 19 years from the Korean National Health and Nutrition Survey collected using the fifth (2010~2012) rotation sample survey were analyzed. Based on the information collected from the survey and dental examination, we determined the associations between the independent (sex and socioeconomic level) and dependent variables using a chi-squared test. Moreover, ordinal logistic regression analyses on multiple categorical values were performed using perceived and objective dental needs as the dependent variables. Results: Generally, factors influencing both perceived and objective dental needs were similar. These included sex, household income, educational level, private insurance, and subjective oral health status. However, the high-income groups had lesser perceived and objective dental needs compared to the low-income groups. Furthermore, factors such as sex, educational level, and marital status had different influence on both needs. Conclusion: Generally, factors that affect perceived and objective dental needs were similar. To minimize unmet dental needs, factors influencing both perceived and objective dental needs should be examined for a broad dental insurance coverage, and efforts to prevent oral diseases are also required.

• Journal of Family Relations
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• v.23 no.1
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• pp.97-120
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• 2018

Objectives: The purpose of this study is to examine the process of how a parent-child relationship affects an impaired objective self, emotional regulation difficulties, and, consequently, interpersonal problems. Methods: To carry out this study, a total of 467 married women were surveyed on their parent-child relationship, impaired objective self, and emotional regulation difficulties. The resulting data was interpreted using descriptive statistics analysis, correlation analysis, and structural equation models analysis. Results: First, the parent-child relationship shows negative correlations with an impaired objective self, emotional regulation difficulties, and interpersonal problems. In addition, an impaired objective self, emotional regulation difficulties, and interpersonal problems show positive correlations with one another. Second, an impaired objective self and emotional regulation difficulties mediate the parent-child relationship and intrapersonal problems consecutively. Conclusions: This indicates that efforts to mitigate an impaired objective self and to intervene in difficulties in emotional regulation can help address intrapersonal difficulties. Finally, this paper examines how this study affects the ongoing discussion on this matter and its implications for future studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.335-352
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• 2023

When solving multi-objective optimization problems, the blindness of the evolution direction of the population gradually emerges with the increase in the number of objectives, and there are also problems of convergence and diversity that are difficult to balance. The many- objective optimization problem makes some classic multi-objective optimization algorithms face challenges due to the huge objective space. The sine cosine algorithm is a new type of natural simulation optimization algorithm, which uses the sine and cosine mathematical model to solve the optimization problem. In this paper, a knee-driven many-objective sine-cosine algorithm (MaSCA-KD) is proposed. First, the Latin hypercube population initialization strategy is used to generate the initial population, in order to ensure that the population is evenly distributed in the decision space. Secondly, special points in the population, such as nadir point and knee points, are adopted to increase selection pressure and guide population evolution. In the process of environmental selection, the diversity of the population is promoted through diversity criteria. Through the above strategies, the balance of population convergence and diversity is achieved. Experimental research on the WFG series of benchmark problems shows that the MaSCA-KD algorithm has a certain degree of competitiveness compared with the existing algorithms. The algorithm has good performance and can be used as an alternative tool for many-objective optimization problems.

• Structural Engineering and Mechanics
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• v.65 no.2
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• pp.173-181
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• 2018

In this paper, finite element (FE) model updating based on multi-objective optimization with the surrogate model for a steel plate girder bridge is investigated. Conventionally, FE model updating for bridge structures uses single-objective optimization with finite element analysis (FEA). In the case of the conventional method, computational burden occurs considerably because a lot of iteration are performed during the updating process. This issue can be addressed by replacing FEA with the surrogate model. The other problem is that the updating result from single-objective optimization depends on the condition of the weighting factors. Previous studies have used the trial-and-error strategy, genetic algorithm, or user's preference to obtain the most preferred model; but it needs considerable computation cost. In this study, the FE model updating method consisting of the surrogate model and multi-objective optimization, which can construct the Pareto-optimal front through a single run without considering the weighting factors, is proposed to overcome the limitations of the single-objective optimization. To verify the proposed method, the results of the proposed method are compared with those of the single-objective optimization. The comparison shows that the updated model from the multi-objective optimization is superior to the result of single-objective optimization in calculation time as well as the relative errors between the updated model and measurement.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.04a
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• pp.143-148
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• 2000

In this article, we presents multi-objective design optimization of laminated composite beam using Fuzzy programming method. At first, the two design objectives are minimizing the structural weight and maximizing the buckling load respectively. Fuzzy multi-optimization problem can be formulated based on results of single optimizations. Due to different relative importance of design objectives, membership functions are constructed by adding exponential parameters for different objective's weights. Finite element analysis of composite beam for buckling behavior are carried by Natural mode method proposed by J.Argyris and computational time of analysis can be reduced. With this scheme, a designer can conveniently obtain a compromise optimal solution of a multi-objective optimization problem only by providing some exponential parameters corresponding to the importance of the objective functions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1802-1814
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• 2012

In order to guide users to select the most optimal access network in heterogeneous wireless networks, a network selection algorithm is proposed which is designed based on multi-objective discrete particle swarm optimization (Multi-Objective Discrete Particle Swarm Optimization, MODPSO). The proposed algorithm keeps fast convergence speed and strong adaptability features of the particle swarm optimization. In addition, it updates an elite set to achieve multi-objective decision-making. Meanwhile, a mutation operator is adopted to make the algorithm converge to the global optimal. Simulation results show that compared to the single-objective algorithm, the proposed algorithm can obtain the optimal combination performance and take into account both the network state and the user preferences.

• International Journal of Aeronautical and Space Sciences
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• v.7 no.1
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• pp.1-12
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• 2006

In this study, a surrogate model is applied to multi-objective aerodynamic optimization design. For the balanced exploration and exploitation, each objective function is converted into the Expected Improvement (EI) and this value is used as fitness value in the multi-objective optimization instead of the objective function itself. Among the non-dominated solutions about EIs, additional sample points for the update of the Kriging model are selected. The present method was applied to a transonic airfoil design. Design results showed the validity of the present method. In order to obtain the information about design space, two data mining techniques are applied to design results: Analysis of Variance (ANOVA) and the Self-Organizing Map (SOM).

• Ocean Systems Engineering
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• v.5 no.2
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• pp.91-107
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• 2015

Ship hull optimization is categorized as a bound, multi variable, multi objective problem with nonlinear constraints. In such analysis, where the objective function representing the performance of the ship generally requires computationally involved hydrodynamic interaction evaluation methods, the objective functions are not smooth. Hence, the evolutionary techniques to attain the optimum hull forms is considered as the most practical strategy. In this study, a parametric ship hull form represented by B-Spline curves is optimized for multiple performance criteria using Genetic Algorithm. The methodology applied to automate the hull form generation, selection of optimization solvers and hydrodynamic parameter calculation for objective function and constraint definition are discussed here.

• Journal of Applied Reliability
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• v.17 no.2
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• pp.150-158
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• 2017

Purpose: The RAM objective is a very important factor that has a great effect on the improvement of the operation ration during the operation maintenance and the reduction of the life cycle cost. It is used as a design criterion during the system development, and its sufficiency should be evaluated during its test evaluation. Method: This study analyzed the cases related to RAM objective setting and suggested the improvement measures. Result: The base data for RAM objective is OMS/MP, which needs to be drawn up under the supervision of the requirement military, and a high-accuracy operating availability should be set through ALDT calculation which reflects the military logistics support environment. In addition, data collection necessary for RAM objective and RAM analysis should be made by supplementing the input data of DELIIS. Conclusion: This study suggests improvement of RAM objective considering for the weapon system.