• 전기학회논문지
• /
• 제58권12호
• /
• pp.2511-2519
• /
• 2009

In this paper, we introduce the methodological system design via feature selection using Principal Component Analysis and Particle Swarm Optimization algorithms. The overall methodological system design comes from three kinds of modules such as preprocessing module, feature extraction module, and recognition module. First, Histogram equalization enhance the quality of image by exploiting contrast effect based on the normalized function generated from histogram distribution values of 2D face image. Secondly, PCA extracts feature vectors to be used for face recognition by using eigenvalues and eigenvectors obtained from covariance matrix. Finally the feature selection for face recognition among the entire feature vectors is considered by means of the Particle Swarm Optimization. The optimized Polynomial-based Radial Basis Function Neural Networks are used to evaluate the face recognition performance. This study shows that the proposed methodological system design is effective to the analysis of preferred face recognition.

• 한국지능시스템학회:학술대회논문집
• /
• 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
• /
• pp.11-12
• /
• 2008

퍼지 시계열 예측은 전체 퍼지 구간에 따른 퍼지 소속 함수의 개수와 범위에 따라서 예측성능에 많은 영향을 미치고 있으며, 이러한 문제점을 개선하기 위한 방법으로 다수 객체들의 학습 및 군집 특성을 이용한 Particle Swarm Optimization기법을 도입하였다. 제안된 방법에서는 군집의 최적 객체를 전체 최적해와 각각의 퍼지 소속 함수들에 대한 최적해로 구분하여 탐색하는 기법을 제안한다. 실제 시계열 데이터를 이용한 실험을 통하여 기존의 연구 결과들과 비교함으로써 제안된 방법의 우수한 성능을 가짐을 검증하였다.

• 대한기계학회논문집B
• /
• 제31권7호
• /
• pp.635-643
• /
• 2007

An inverse radiation analysis is presented for the estimation of the radiation properties for an absorbing, emitting, and scattering media with diffusely emitting and reflecting opaque boundaries. In this study, a repulsive particle swarm optimization(RPSO) algorithm which is a relatively recent heuristic search method is proposed as an effective method for improving the search efficiency for unknown parameters. To verify the performance of the proposed RPSO algorithm, it is compared with a basic particle swarm optimization(PSO) algorithm and a hybrid genetic algorithm(HGA) for the inverse radiation problem with estimating the various radiation properties in a two-dimensional irregular medium when the measured temperatures are given at only four data positions. A finite-volume method is applied to solve the radiative transfer equation of a direct problem to obtain measured temperatures.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권2호
• /
• pp.442-460
• /
• 2021

Nowadays, recommendation systems (RSs) are applied to all aspects of online life. In order to overcome the problem that individuals who do not meet the constraints need to be regenerated when the many-objective evolutionary algorithm (MaOEA) solves the hybrid recommendation model, this paper proposes a many-objective particle swarm optimization algorithm based on multiple criteria (MaPSO-MC). A generation-based fitness evaluation strategy with diversity enhancement (GBFE-DE) and ISDE⁺ are coupled to comprehensively evaluate individual performance. At the same time, according to the characteristics of the model, the regional optimization has an impact on the individual update, and a many-objective evolutionary strategy based on bacterial foraging (MaBF) is used to improve the algorithm search speed. Experimental results prove that this algorithm has excellent convergence and diversity, and can produce accurate, diverse, novel and high coverage recommendations when solving recommendation models.

• Structural Engineering and Mechanics
• /
• 제42권3호
• /
• pp.335-352
• /
• 2012

Particle Swarm Optimization (PSO) is a stochastic population based optimization algorithm which has attracted attentions of many researchers. This method has great potentials to be applied to many optimization problems. Despite its robustness the standard version of PSO has some drawbacks that may reduce its performance in optimization of complex structures such as laminated composites. In this paper by suggesting a new variation scheme for acceleration parameters and inertial weight factors of PSO a novel optimization algorithm is developed to enhance the basic version's performance in optimization of laminated composite structures. To verify the performance of the new proposed method, it is applied in two multi-objective design optimization problems of laminated cylindrical. The numerical results from the proposed method are compared with those from two other conventional versions of PSO-based algorithms. The convergancy of the new algorithms is also compared with the other two versions. The results reveal that the new modifications inthe basic forms of particle swarm optimization method can increase its convergence speed and evade it from local optima traps. It is shown that the parameter variation scheme as presented in this paper is successful and can evenfind more preferable optimum results in design of laminated composite structures.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2009년도 춘계학술대회
• /
• pp.185-188
• /
• 2009

이 논문에서는 PID 알고리즘을 이용하여 시소 시스템의 균형을 위한 위치 제어기를 설계하고자 한다. 시소 시스템은(Seesaw System) 선박 및 항공 역학, 도립진자, 각종 분석, 로봇 시스템 등의 해석에 광범위하게 응용되는 시스템이자 현대 제어 시스템의 이론과 각종 응용문제를 취급할 수 있는 장치이다. 시소 시스템의 경우 시스템이 비선형성이 강한 제어 대상이므로 시스템의 이해와 해석, 그리고 파라미터의 정확한 선정이 필수요소이다. 사용할 시스템 제어 알고리즘에는 간단하고 오랜 역사를 통해 안정성이 보장된 PID 알고리즘과 정확하고 빠른 PID 파라미터 동조에 필요한 연산 최적화 알고리즘인 PSO(Particle Swarm Optimization) 통해 외란이나 제어기의 변화에 빠르게 적응할 수 있도록 하여 성능과 안정성을 보장한다.

• 대한전자공학회논문지TC
• /
• 제46권1호
• /
• pp.1-9
• /
• 2009

OFDM(Orthogonal Frequency Division Multiplexing) 시스템은 주파수 선택적 페이딩(frequency selective fading)과 협대역 간섭(narrowband interference)에 강한 전송 방식으로 대용량 데이터 통신에 적합하다. 하지만 독립적으로 변조된 많은 부반송파들의 중첩으로 신호의 진폭이 증가하여 PAPR(Peak-to-Average Power Ratio)이 증가하는 문제가 발생한다. PAPR 문제를 해결하기 위해 제안된 PTS(Partial Transmit Sequence) 기법은 OFDM 신호를 부블록으로 나눈 후 위상 가중치를 곱하여 PAPR을 감소시킬 수 있지만, 위상 가중치를 탐색하는 과정에서 계산의 복잡도가 부블록 수에 따라 지수적으로 증가하는 단점이 있다. 본 논문에서는 PTS 기법의 위상 탐색 과정에 최적화 기법인 변형된 Greedy 알고리즘과 PSO(Particle Swarm Optimization) 알고리즘을 조합한 MG-PSO(Modified Greedy algorithm-Particle Swarm Optimization) 알고리즘을 적용한 구조를 제안하였다. 이 구조는 PTS 기법의 위상 탐색 과정에서 계산 복잡도가 지수적으로 증가하는 문제를 해결하고 PAPR 감소 성능도 보장할 수 있다. 제안하는 알고리즘을 통신 시스템에 적용하였을 때 PAPR 감소 성능을 분석하였다.

• 대한기계학회논문집B
• /
• 제38권9호
• /
• pp.747-755
• /
• 2014

광자(Photon)이나 전자기파(Electromagnetic Wave) 등의 형태로 직접 열을 전달하는 특징을 가지고 있는 복사열전달은 중간 매질의 열전달 관여여부에 따라 표면복사(Surface Radiation)와 기체복사(Gas Radiation)의 형태로 구분될 수 있다. 본 연구에서는 원통 형상에서의 표면복사에 대해 미지의 복사물성치들을 역해석 방법을 이용해 역추정하였다. 이때, 효율적인 역해석을 위해 반발 입자 군집 최적화(Repulsive Particle Swarm Optimization, RPSO) 알고리즘을 역해석 기법으로 채택하였다. 이로부터 얻은 해의 수렴성과 정확도 등을 기존의 유전알고리즘(GA) 결과와 비교해 봄으로써, 표면복사 현상에 대한 역해석의 적용 가능성을 고찰하고자 하였다.

• 정보통신설비학회논문지
• /
• 제11권2호
• /
• pp.34-38
• /
• 2012

In this paper, the particle swarm optimization (PSO) algorithm is adopted to design a modified ring-slot type patch rectenna with a resonance frequency of 2.45GHz. In order to accomplish minimization of dimensions and circular polarization (CP) and harmonic suppression, axial direction slits and side-cuts are added to the patch of the ring. The PSO manipulated this kind of multi-dimensional problem very well, and as a result, the designed rectenna shows a desirable performance of return loss of 21.36dB and axial ratio of 2.92dB at the frequency of 2.45GHz with compact sizing.

• 제어로봇시스템학회논문지
• /
• 제12권4호
• /
• pp.328-338
• /
• 2006

A new evolutionary computation technique, called particle swarm optimization(PSO), has been proposed and introduced recently. PSO has been inspired by the social behavior of flocking organisms, such as swarms of birds and fish schools and PSO is an algorithm that follows a collaborative population-based search model. Each particle of swarm flies around in a multidimensional search space looking for the optimal solution. Then, Particles adjust their position according to their own and their neighboring-particles experience. In this paper, characteristics of PSO such as mentioned are reviewed and compared with GA which is based on the evolutionary mechanism in natural selection. Also dimensionalities of PSO and GA are compared throughout numeric experimental studies. The comparative studies demonstrate that PSO is characterized as simple in concept, easy to implement, and computationally efficient and can generate a high-quality solution and stable convergence characteristic than GA.