• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.498-499
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• 2008

신재생에너지의 개발, 정부의 규제 완화와 환경적 이유로 인해 배전계통에서 분산전원은 점차 증가하는 추세이다. 최근 분산전원을 소유한 구역전기사업자가 전력시장의 새로운 시장 참여자로서 대두되고 있다. 분산전원을 소유한 구역전기사업자는 최대 이윤을 얻기 위해서 매 시간마다 발전량을 변화시켜야 한다. 본 논문에서는 배전계통에 연계된 분산전원의 최적 운영에 대해서 소개할 것이다. 이 때, 최적화의 목적은 구역전기사업자 이윤의 최대화이며, 국제적 환경규제에 따른 온실가스배출량을 고려하여 발전비용을 산출한다. 산출기법으로 Particle Swarm Optimization 알고리즘을 이용한다.

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.476-483
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• 2008

This paper is aimed at presenting techniques of hybrid differential evolution for solving various kinds of Economic Dispatch(ED) problems such as those including prohibited zones, emission dispatch, multiple fuels, and multiple areas. The results obtained for typical problems are compared with those obtained by other techniques such as Particle Swarm Optimization(PSO) and Classical Evolutionary Programming(CEP) techniques. The comparison of the results proves that hybrid differential evolution is quite favorable for solving ED problems with no restrictions on the shapes of the input-output functions of the generator.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1887-1888
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• 2008

본 논문에서는 퍼지 추론 기반의 다항식 RBF 뉴럴네트워크(Polynomial Radial Basis Function Neural Network; pRBFNN)를 설계하고 PSO(Particle Swarm Optimization) 알고리즘을 이용하여 모델의 파라미터를 동정한다. 제안된 모델은 "IF-THEN" 형식으로 기술되는 퍼지 규칙에 의해 조건부, 결론부, 추론부의 기능적 모듈로 표현된다. 조건부의 입력공간 분할에는 HCM 클러스터링에 기반을 두어 구조가 결정되며, 기존에 주로 사용된 가우시안 함수를 RBF로 이용하고, 원뿔형태의 선형 함수를 제안한다. 또한 입력공간 분할시 데이터 집합의 특성을 반영하기 위해 분포상수를 각 입력마다 고려하여 설계함으로서 공간 분할의 정밀성을 높인다. 결론부에서는 기존 상수항의 연결가중치를 다항식 형태로 표현하는 pRBFNN을 제안한다. 제안한 모델의 성능을 평가하기 위해 Box와 Jenkins가 사용한 가스로 시계열 데이터를 적용하고, 기존 모델과의 근사화와 일반화 능력에 대하여 토의한다.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1365-1366
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• 2015

본 논문에서는 HOG 특징을 이용한 다항식 방사형 기저함수 신경회로망 기반 숫자 인식 시스템의 설계를 제안한다. 제안한 숫자 인식 시스템은 HOG 특징을 이용하여 숫자를 입력 데이터로 사용하기 위해 특징을 계산한다. 다항식 방사형 기저 함수 신경회로망은 고차원 데이터의 입-출력 형태를 갖는 클래스를 분류하는데 용이하며, 활성함수의 중심점 및 분포상수는 Fuzzy C-Means(FCM) 알고리즘에 의해 초기 값을 설정한다. 또한 제안한 분류기의 최적화를 위해 Particle Swarm Optimization(PSO)를 사용하여 최적화된 분류기의 성능을 비교한다. 숫자 인식을 위하여 공인 데이터베이스인 MNIST handwritten digit database를 사용하여 분류기의 성능을 평가하고 분석한다.

• Journal of Computing Science and Engineering
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• v.8 no.2
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• pp.87-93
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• 2014

Coronary artery disease (CAD) is currently a prevalent disease from which many people suffer. Early detection and treatment could reduce the risk of heart attack. Currently, the golden standard for the diagnosis of CAD is angiography, which is an invasive procedure. In this article, we propose an algorithm that uses data mining techniques, a fuzzy expert system, and the imperialist competitive algorithm (ICA), to make CAD diagnosis by a non-invasive procedure. The ICA is used to adjust the fuzzy membership functions. The proposed method has been evaluated with the Cleveland and Hungarian datasets. The advantage of this method, compared with others, is the interpretability. The accuracy of the proposed method is 94.92% by 11 rules, and the average length of 4. To compare the colonial competitive algorithm with other metaheuristic algorithms, the proposed method has been implemented with the particle swarm optimization (PSO) algorithm. The results indicate that the colonial competition algorithm is more efficient than the PSO algorithm.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.43-44
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• 2014

본 논문에서는 유전알고리즘의 유전자형-표현형을 사용한 수정된 이진 입자군집최적화의 두 번째 버전을 소개한다. 첫 번째 버전의 수정된 이진 입자군집최적화는 위치 정보에 유전학의 표현형을 사용한 반면에 제안하는 버전은 유전학의 유전자형을 사용한다. 이진 정보만을 제공하는 표현형에 비해 연속 공간 전체를 탐색공간으로 제공하는 유전자형 정보를 사용하여 해 공간을 보다 넓은 공간으로 만들 수 있다. 10개의 실험 평가 함수에 실험한 결과, 두 번째 버전은 탐색 공간이 넓고 지역최적해가 많은 함수에서 우수한 결과를 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1588-1603
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• 2014

In space diversity combining, conventional methods such as maximal ratio combining (MRC), equal gain combining (EGC) and selection combining (SC) are commonly used to improve the output signal-to-noise ratio (SNR) provided that the channel is perfectly estimated at the receiver. However, in practice, channel estimation is often imperfect and this indeed deteriorates the system performance. In this paper, diversity combining techniques based on two evolutionary algorithms, namely genetic algorithm (GA) and particle swarm optimization (PSO) are proposed and compared. Numerical results indicate that the proposed methods outperform the conventional MRC, EGC and SC methods when the channel estimation is imperfect while it shows similar performance as that of MRC when the channel is perfectly estimated.

• Journal of the Optical Society of Korea
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• v.15 no.2
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• pp.187-195
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• 2011

We have designed two photonic crystal waveguide (PCW) structures with output focused beams in order to achieve more coupling between photonic devices and decrease the mismatch losses in photonic integrated circuits. PCW with coupled resonator optical waveguide (CROW) termination has been optimized by both one dimensional (1D) and seven dimensional (7D) particle swarm optimization (PSO) algorithms by evaluating the fitness function by the finite difference time domain (FDTD) method. The 1D and 7D-optimizations caused the factors of 2.79 and 3.875 improvements in intensity of the main lobe compared to the non-optimized structure, whereas the FWHM in 7D-optimized structure was increased, unlike the 1D case. It has also been shown that the increment of focusing causes decrement of the bandwidth.

• International Journal of CAD/CAM
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• v.9 no.1
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• pp.85-91
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• 2010

In this paper, we demonstrate an autonomous design of motion control of virtual creatures (called animated robots in this paper) and develop modeling software for animated robots. An animated robot can behave autonomously by using its own sensors and controllers on three-dimensional physically modeled environment. The developed software can enable us to execute the simulation of animated robots on physical environment at any time during the modeling process. In order to simulate more realistic world, an approximate fluid environment model with low computational costs is presented. It is shown that a combinatorial use of neural network implementation for controllers and the genetic algorithm (GA) or the particle swarm optimization (PSO) is effective for emerging more realistic autonomous behaviours of animated robots.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.318-323
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• 2016

In the current study, factors affecting cheese brands products in grocery stores were evaluated with an emphasis on diversity. The sample data were collected from Noushad and Pegah Milk Industry in 2015 and data were extracted, reviewed, and analyzed from 435 grocery stores in Mashhad using seemingly unrelated regression model and particle swarm optimization algorithm. Results showed that optimum amount of Kalleh product diversity is higher than other competitors in the market, and Kalleh UF diversity is 100 to 250 grams, and Kalleh UF diversity with weight of 300 to 500 grams is more than other modes of diversity, and Kalleh brand must remove tin cheese from the market. Sabah Brand also should eliminate its glass and creamy diversity from market, UF diversity is mostly welcomed in market.