• Journal of Power Electronics
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• v.15 no.4
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• pp.1119-1130
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• 2015

This study investigates the multi-objective fuzzy optimization of crowbar resistance for the doubly fed induction generator (DFIG) low-voltage ride-through (LVRT). By integrating the crowbar resistance of the crowbar circuit as a decision variable, a multi-objective model for crowbar resistance value optimization has been established to minimize rotor overcurrent and to simultaneously reduce the DFIG reactive power absorbed from the grid during the process of LVRT. A multi-objective genetic algorithm (MOGA) is applied to solve this optimization problem. In the proposed GA, the value of the crowbar resistance is represented by floating-point numbers in the GA population. The MOGA emphasizes the non-dominated solutions and simultaneously maintains diversity in the non-dominated solutions. A fuzzy-set-theory-based is employed to obtain the best solution. The proposed approach has been evaluated on a 3 MW DFIG LVRT. Simulation results show the effectiveness of the proposed approach for solving the crowbar resistance multi-objective optimization problem in the DFIG LVRT.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.10
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• pp.2150-2158
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• 2002

A recent research and development has the requirement for the optimization to shorten design time of modified or new product model and to obtain more precise engineering solution. General optimization problem must consider many conflicted objective functions simultaneously. Multi-objective optimization treats the multiple objective functions and constraints with design change. But, real engineering problem doesn't describe accurate constraint and objective function owing to the limit of representation. Therefore this study applies variance analysis on the basis of structure analysis and DOE to the vertical roller mill fur portland cement and proposed statistical design model to evaluate the effect of structural modification with design change by performing practical multi-objective optimization considering mass, stress and deflection.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.97-110
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• 2021

Fog can cause large-scale human and economic damages, including traffic systems and agriculture. So, Korea Meteorological Administration is operating about 290 visibility meters to improve the observation level of fog. However, it is still insufficient to detect very localized fog. In this study, high-resolution grid-type visibility data were retrieved from irregularly distributed visibility data across the country. To this end, three objective analysis techniques (Inverse Distance Weighting (IDW), Ordinary Kriging (OK) and Universal Kriging (UK)) were used. To find the best method and parameters, sensitivity test was performed for the effective radius, power parameter and variogram model that affect the level of objective analysis. Also, the effect of data distribution characteristics (level of normality) on the performance level of objective analysis was evaluated. IDW showed a relatively high level of objective analysis in terms of bias, RMSE and correlation, and the performance is inversely proportional to the effective radius and power parameter. However, the two Krigings showed relatively low level of objective analysis, in particular, greatly weakened the variability of the variables, although the level of output was different depending on the variogram model used. As the level of objective analysis is greatly influenced by the distribution characteristics of data, power, and models used, care should be taken when selecting objective analysis techniques and parameters.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.127-135
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• 2008

Generally, optimum shortest path algorithms adopt single attribute objective among several attributes such as travel time, travel cost, travel fare and travel distance. On the other hand, multi-objective shortest path algorithms find the shortest paths in consideration with multi-objectives. Up to recently, the most of all researches about multi-objective shortest paths are proceeded only in single transportation mode networks. Although, there are some papers about multi-objective shortest paths with multi-modal transportation networks, they did not consider transfer problems in the optimal solution level. In particular, dynamic programming method was not dealt in multi-objective shortest path problems in multi-modal transportation networks. In this study, we propose a multi-objective shortest path algorithm including dynamic programming in order to find optimal solution in multi-modal transportation networks. That algorithm is based on two-objective node-based label correcting algorithm proposed by Skriver and Andersen in 2000 and transfer can be reflected without network expansion in this paper. In addition, we use non-dominated paths and tree sets as labels in order to improve effectiveness of searching non-dominated paths. We also classifies path finding attributes into transfer and link travel attribute in limited transit networks. Lastly, the calculation process of proposed algorithm is checked by computer programming in a small-scaled multi-modal transportation network.

• Journal of Korean Elementary Science Education
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• v.37 no.4
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• pp.440-454
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• 2018

This study aims to compare student self-, teacher-, and objective assessments of elementary science-gifted students' scientific creativity. A science-gifted program on the topic of Hydraulic Machine was implemented to 40 fifth-graders in the Science-Gifted Education Center of an education office in Seoul, Korea for four weeks. The products of the students' activities were assessed by three types of 'Student Self-Assesment', 'Teacher-Assesment', and 'Objective Assessment using Formula'. Based on two essential components of creativity, the scientific creativity is divided into two parts of originality and usefulness. Ideas that satisfy both components can be counted as scientifically creative. The main results of this study are as follows: First, the scores of each week and the average of the overall four-week scores on scientific creativity were significantly correlated. Student self-assessment (r=.687), teacher-assessment (r=.715), and objective assessment (r=.724) appeared consistently over instructional periods. Second, the average scores of student self-, objective, and teacher-assessments were 73.15, 35.72, and 26.60, respectively. The result of student self-assessment on scientific creativity tended to be higher than those of formula and teacher. Third, among the three types of assessment on scientific creativity, a strong correlation appeared between teacher- and objective assessment (r=.974), but neither between student self- and objective (r=.161) nor between student self- and teacher- (r=.213). Fourth, the scores on originality component had a positive correlation between teacher- and objective assessment (r=.713). The scores of student self- and teacher-assessments had a significant correlation too (r=.315), but not between student self- and objective assessment (r=.279). Fifth, the scores on usefulness component did not have a significant correlation between student self- and teacher-assessment (r=.155). Sixth, there was no significant difference on scientific creativity between student self- and objective assessment [${\chi}^2$(1, n=40)=1.667, p<.197]. Not between student self- and teacher-assessment either [${\chi}^2$(1, n=40)=1.616, p<.204]. On the contrary, there was a significant difference between teacher- and objective assessment [${\chi}^2$(1, n=40)=32.593, p<.000]. Seventh, the students were categorized into four groups according to the levels of their scores by student self- and teacher-assessment. The result showed that factors influencing student self-assessment are inherent in the personality traits of gifted individuals, such as self-esteem and perfectionism. The findings suggested that there are challenges for the educators to make efforts to construct consistent assessment methods for scientific creativity.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.601-608
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• 2007

Lee, et al. (1999) proposed a unique but universal robust objective function replacing the square objective function for the radial basis function network, and demonstrated some advantages. In this article, the robust objective function in Lee, et al. (1999) is adapted for a multilayer perceptron (MLP). The shape of the robust objective function is formed by the scale parameter. Another method of determining a proper value of that parameter is proposed.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.511-513
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• 2003

멀티미디어 서비스의 증가로 다양한 QoS(Quality of Service) 파라미터를 보장하는 멀티캐스트 라우팅 알고리즘이 필요하게 되었다. 이러한 멀티캐스트 라우팅에서 고려해야 하는 각각의 QoS 파리미터와 비용과의 관계는 Trade-off 관계에 있으며, 이들을 동시에 최적화하는 멀티캐스트 라우팅 문제는 다목적 최적화 문제(Multi-Objective Optimization Problem: MOOP)에 속하는 어려운 문제이다. 다목적 최적화 문제의 목표는 다양한 파레토 최적해(Pareto Optimal Solution)를 찾는데 있으며, 이를 해결하기 위해서 본 논문에서는 다목적 유전자 알고리즘(Multiple Objective Genetic Algorithms： MOGA)을 적용하였다.

• The Pure and Applied Mathematics
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• v.3 no.1
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• pp.73-81
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• 1996

Multiple objective programming has been a popular research area since 1970. The pervasiveness of multiple objective in decision problems have led to explosive growth during the 1980's. Several approaches (interactive methods, feasible direction methods, criterion weight space methods, Lagrange multiplies methods, etc) have been developed for solving decision problems having multiple objectives. However there are still many mathematically challengings including multiple objective integer, nonlinear optimization problems which require further mathematically oriented research. (omitted)

• Journal of Korea Water Resources Association
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• v.38 no.9 s.158
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• pp.737-746
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• 2005

Optimization is a process that searches an optimal solution to obtain maximum or minimum value of an objective function. Many researchers have focused on effective search algorithms for the optimum but few researches were interested in establishing the objective function. This study compares two approaches for the objective function: one allows a tradeoff among the objectives and the other does not allow a tradeoff by assigning weights for the absolute priority between the objectives. An optimization model using sampling stochastic dynamic programming was applied to these two objective functions and the resulting optimal policies were compared. As a result, the objective function with no tradeoff provides a decision making process that matches practical reservoir operations than that with a tradeoff allowed. Therefore, it is more reasonable to establish the objective function with no a tradeoff among the objectives for multi-purpose dam operation plan in Korea.

• Journal of the Economic Geographical Society of Korea
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• v.5 no.2
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• pp.209-228
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• 2002

The purpose of this paper is to evaluate strategies for the attraction of Korean finns into EU Objective 1 (less prosperous region).2(regions facing structural difficulties or conversion) on the basis of Korean foreign direct investment in the European Union(EU) in the past 10 years (the late 1980s-late 1990s). Of such strategies the most important was incentive packages for Korean finns by those regions. Nonetheless, these packages did not contribute to the development of the finns and regions because of limits to the finns' competitiveness(cost competitiveness) and the regions' competitiveness(low productivity and skills). Consequently, these strategies of EU Objective 1.2 regions did not provide an opportunity for pathways to successful development because the incentive packages provided to the finns and regions without the consideration of their internal and external circumstances.