• 한국전자통신학회논문지
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• 제18권1호
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• pp.11-22
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• 2023

평면 능동위상배열안테나 시스템에 있어, 간소화된 방사특성 측정 절차를 가지는 방사소자 결함진단 기법을 제시하였다. 이를 위해 평면 배열 구성에 대한 방사특성을 기반으로 선형 배열 구성으로 근사화 분석할 수 있는 방법 및 방사소자 결함진단과정에서 발생할 수 있는 유일해 문제를 해소하기 위한 방법을 연구하였다. 본 논문에서 제시된 기법 및 유전 알고리즘을 기반으로 다양한 평면 능동위상배열안테나 구성에 따른 방사소자 결함진단에 대한 모의실험을 수행하였다. 모의실험 결과, 제시된 방사소자 결함진단 기법은 다양한 구성을 가지는 평면 능동위상안테나에 대해서도 적용가능함을 확인하였다.

• 대한수학교육학회지:수학교육학연구
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• 제13권3호
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• pp.351-364
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• 2003

Clairaut의 <기하학 원론>은 Euclid의 <원론>의 논리-연역적인 전개 방식에 대항하여 역사발생적 원리에 입각하여 쓰여진 최초의 기하 교재이다. 본 논문은 <기하학 원론>을 고찰함으로써 Clairaut가 생각한 역사발생적 원리를 파악하고, 아울러 학교 수학에의 적용 방안을 탐색하는 것을 목표로 한다. 이를 위해, <기하학 원론>의 내용 전개 방식으로부터 저자의 기본 아이디어에서 비롯된 다섯 가지 특징을 추출한다. 필요에 의한 기하의 출현, 실생활 문제 해결을 통한 접근, 초보자에게 자연스런 방법으로서 직관적 요소와 논리적 요소의 조화, 기본 원리의 파악, 활동적 원리의 구현. 이러한 특징은 Clairaut의 역사발생적 원리를 구체적으로 드러내며, 기하 영역의 교재 구성 및 교수 실제를 위한 시사점을 제공한다. 그리고, 학교 기하에서 매우 유용한 두 개의 정리를 예로 들어 그의 역사발생적 원리를 재음미한다.

• 한국산학기술학회논문지
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• 제15권10호
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• pp.6276-6281
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• 2014

유전자 알고리즘은 탐색과 최적화 문제에 대한 효과적인 방법으로 이용되고 있으나 다수의 정점이 있는 다중정점 함수에 대한 응용에 있어서는 지역해에 조기 수렴하여 고착되는 등 전역 최적해를 찾는데 어려움이 있다. 이러한 문제는 탐색공간을 충분히 탐색할 수 있는 모집단의 다양성이 부족한 데 기인하는 것이며 해결방법으로 니칭 방법과 크라우딩 방법 등이 소개되고 있다. 개체군의 다양성을 증가시키는 방법으로 지역해에 고착되지 않고 전역 최적해로 수렴되도록 하는 데 기본을 두고 있다. 본 논문에서는 다중정점 함수의 전역 최적해에 수렴하고 수렴속도를 높이는 방법으로 진화과정의 매 세대마다 탐색영역에 충분히 분포되도록 임의로 생성된 보조 모집단을 공급함으로서 안정적으로 전역 최적해로 수렴하는 방법을 제안하였다. 컴퓨터 모의실험을 통하여 본 논문에서 제안한 방법을 입증하였다.

• Interdisciplinary Bio Central
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• 제6권4호
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• pp.2.1-2.7
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• 2014

Sexual dimorphism in intelligence suggests that this phenotype is a sexually selected trait. This view is supported by an overrepresentation (compared to the autosomal genome) of genes affecting cognition on the X chromosome. The aim of this study is to test the hypothesis that sexual selection can explain sex and country-level differences in performance on tests of fluid intelligence. Nationally representative samples from N = 44 countries were obtained from the Programme for International Student Assessment (PISA) Creative Problem Solving (CPS), which evaluates the core of intelligence, that is novel problem solving ability. Sexual selection has the double effect of increasing the prevalence of a favored phenotype and reducing genetic variation in sexually selected traits. Matching these predictions from evolutionary theory, the average country fluid intelligence is positively correlated to sexual dimorphism after partialling out per capita GDP and the latter in turn is inversely correlated to variance in intelligence scores within populations. Males have a higher variance than females but there is a negative correlation between male-female difference in variance and sexual dimorphism in intelligence, suggesting that selection reduces variance more in the selected sex. Average country male height is negatively correlated to sexual dimorphism in intelligence, a fact that supports the notion of a trade-off between physical and intellectual competition in the context of access to females. The results of this study, if replicated, imply that genome-wide association studies of cognition may benefit from a focus on sex chromosomes, which so far have been neglected. Another implication of this study is that intelligence has continued to evolve after different human populations migrated out of Africa and possibly up to the 19th century, as suggested by the substantial variability in sex differences even between neighbouring countries.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권2호
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• pp.233-238
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• 2003

Living creatures maintain their variety through speciation, which helps them to have more fitness for an environment. So evolutionary algorithm based on biological evolution must maintain variety in order to adapt to its environment. In this paper, we utilize the concept of speciation. Each individual of population creates their offsprings using mutation, and next generation consists of them. Each individual explores search space determined by mutation. Useful search space is extended by differentiation, then population explorers whole search space very effectively. If evolvable hardware evolves through mutation, it is useful way to explorer search space because of less varying inner structure. We verify the effectiveness of the proposed method by applying it to two optimization problems.

• 대한전기학회논문지:전력기술부문A
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• 제50권11호
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• pp.520-527
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• 2001

This paper suggests a new methodology of evolutionary computations - an Adaptive Evolutionary Algorithm (AEA) for solving the Economic Load Dispatch (ELD) problem which has piecewise quadratic cost functions and prohibited operating zones with many local minima. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and the population by ES are adaptively modulated according to the fitness. Case studies illustrate the superiority of the proposed methods to existing conventional methods in power generation cost and computation time. The results demonstrate that the AEA can be applied successfully in the solution of ELD with piecewise quadratic cost functions and prohibited operating zones

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.396-398
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• 2003

This paper presents the scheme for load model based dispersed generation system (DGs) installation and operation in unbalanced distribution systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load. The main idea of solving fuzzy nonlinear goal programming is to transform the original objective function and constraints into the equivalent multiple objective functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithms. The method proposed was applied to IEEE 13 bus test systems to demonstrate its effectiveness.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2339-2341
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• 1998

This paper is concerned with an energy optimization for the walking of IWR biped robot. The movement of balancing joints are determined by ZMP(Zero Moment Point) and dynamic properties caused by motion of a swing leg. Therefore, ZMP positions have an important role in walking and guarnateeing the stability of a robot. A genetic algorithm is utilized for solving this problem and finding ZMP with a minimum energy at each sampling time during the walk. In this study, we performed an energy optimization with desired ZMP trajectories and motion of balancing joints.

• 대한전기학회논문지:전력기술부문A
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• 제49권2호
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• pp.70-77
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• 2000

This paper proposes a method of solving a unit commitment problem using tabu search (TS) which is heuristic algorithm. Ts is a local search method that starts from any initial solution and attempts to determine a better solution using memory structures. In this paper, to reduce the computation time for finding the optimal solution, changing tabu list size as intensification strategy and path relinking method as diversification strategy are proposed. To show the usefulness of the proposed method, we simulated for 10 units system and 110 units system. Numerical results show improvements in the generation costs and the computation time compared with priority list, genetic algorithm(GA), and hybrid GA.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회B
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• pp.2122-2125
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• 2008

Because the reheating furnace consumes a large amount of energy to heat up the slabs, it is very important to find an optimal temperature patterns in the furnace for energy saving as well as uniform target temperature at the exit of the furnace. In this study, the temperature profiles in the slab are determined by solving the transient one-dimensional heat conduction equation in conjunction with boundary conditions with total heat exchange factors. The optimal temperature patterns are obtained to minimize the fuel consumption with satisfying the predetermined constraint conditions. The design optimization is performed by using a genetic algorithm and the optimal results are validated with results obtained from the PIDO tool, called as P.I.A.n.O.