• 제목/요약/키워드: differential evolutionary method

검색결과 29건 처리시간 0.026초

차분진화 알고리즘을 이용한 Nearest Prototype Classifier 설계 (Design of Nearest Prototype Classifier by using Differential Evolutionary Algorithm)

  • 노석범;안태천
    • 한국지능시스템학회논문지
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    • 제21권4호
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    • pp.487-492
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    • 2011
  • 본 논문에서는 가장 단순한 구조를 가진 Nearest Prototype Classifier의 성능 개선을 위해 차분 진화 알고리즘을 적용하여 prototype의 위치를 결정하는 방법을 제안하였다. 차분 진화 알고리즘을 이용하여 prototype의 위치 벡터가 결정이 되며, 차분 진화 알고리즘에 의해 결정된 prototype의 class label을 결정하기 위한 class label 결정 알고리즘도 제안하였다. 제안된 알고리즘의 성능 평가를 위해 기존의 패턴 분류기와 비교 결과를 보인다.

차분진화 알고리즘을 이용한 지역 Linear Discriminant Analysis Classifier 기반 패턴 분류 규칙 설계 (Design of Pattern Classification Rule based on Local Linear Discriminant Analysis Classifier by using Differential Evolutionary Algorithm)

  • 노석범;황은진;안태천
    • 한국지능시스템학회논문지
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    • 제22권1호
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    • pp.81-86
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    • 2012
  • 본 논문에서는 전형적인 Linear Discriminant Analysis을 확장시켜 전체 입력공간을 다수의 지역공간으로 분할하고 분할된 공간에 Local Linear Discriminant Analysis 기반으로 하여 패턴 분류 규칙을 설계하는 새로운 방법을 제안한다. 전체 입력공간을 여러 개의 지역공간으로 분할하기 위한 방법으로 unsupervised clustering의 대표적인 방법인 k-Means 클러스터링 기법과 최적화 알고리즘인 차분 진화 연산 알고리즘을 사용한다. 제안된 알고리즘의 성능 평가를 위해 기존의 패턴 분류기와 비교 결과를 제시한다.

Differential Evolution Algorithm for Job Shop Scheduling Problem

  • Wisittipanich, Warisa;Kachitvichyanukul, Voratas
    • Industrial Engineering and Management Systems
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    • 제10권3호
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    • pp.203-208
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    • 2011
  • Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

진화 알고리즘기반의 SI기법을 이용한 외부 프리스트레싱으로 보강된 텐던의 장력 추정 (Estimation of External Prestressing Tendon Tension Using Sl Technique Based on Evolutionary Algorithm)

  • 장한택;노명현;이상열;박대효
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2008년도 정기 학술대회
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    • pp.156-159
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    • 2008
  • This paper introduces a remained tensile force estimation method using SI technique based on evolutionary algorithm for externally prestressed tendon. This paper applies the differential evolutionary scheme to SI technique. A virtual model test using ABAQUS 3 dimensional frame model has been made for this work The virtual model is added to the tensile force(28.5kN). Two set of frequencies are extracted respectively from the virtual test and the self-coding FEM 2 dimension model. The estimating tendon tension for the FEM model is 28.31kN. It is that the error in the tendon tension is 1% through the differential evolutionary algorithm. The errors between virtual model and the self-coding FEM model are assumed as the model error.

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철도차량을 위한 퍼지모델기반 최적 경제운전 패턴 개발 (Optimal Economical Running Patterns Based on Fuzzy Model)

  • 이태형;황희수
    • 한국지능시스템학회논문지
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    • 제16권5호
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    • pp.594-600
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    • 2006
  • 본 논문은 전기철도차량의 운행시간 여유분을 고려하여 에너지 소비를 최소화하는 경제운전 패턴을 찾는 방안을 제시하였다. 경제최고속도와 타행끝점속도를 주행패턴의 변수로 사용하여 퍼지모델을 구축하고 이를 대상으로 진화 탐색을 적용하여 최적의 경제운전 패턴을 찾아낼 수 있으며, 사례연구를 통해 이를 입증하였다.

A PREDICTOR-CORRECTOR METHOD FOR FRACTIONAL EVOLUTION EQUATIONS

  • Choi, Hong Won;Choi, Young Ju;Chung, Sang Kwon
    • 대한수학회보
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    • 제53권6호
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    • pp.1725-1739
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    • 2016
  • Abstract. Numerical solutions for the evolutionary space fractional order differential equations are considered. A predictor corrector method is applied in order to obtain numerical solutions for the equation without solving nonlinear systems iteratively at every time step. Theoretical error estimates are performed and computational results are given to show the theoretical results.

개선된 미분 진화 알고리즘에 의한 퍼지 모델의 설계 (Design of Fuzzy Models with the Aid of an Improved Differential Evolution)

  • 김현기;오성권
    • 한국지능시스템학회논문지
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    • 제22권4호
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    • pp.399-404
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    • 2012
  • Evolutionary algorithms such as genetic algorithm (GA) have been proven their effectiveness when applying to the design of fuzzy models. However, it tends to suffer from computationally expensWive due to the slow convergence speed. In this study, we propose an approach to develop fuzzy models by means of an improved differential evolution (IDE) to overcome this limitation. The improved differential evolution (IDE) is realized by means of an orthogonal approach and differential evolution. With the invoking orthogonal method, the IDE can search the solution space more efficiently. In the design of fuzzy models, we concern two mechanisms, namely structure identification and parameter estimation. The structure identification is supported by the IDE and C-Means while the parameter estimation is realized via IDE and a standard least square error method. Experimental studies demonstrate that the proposed model leads to improved performance. The proposed model is also contrasted with the quality of some fuzzy models already reported in the literature.

Phase Transitions and Phase Diagram of the Island Model with Migration

  • Park, Jeong-Man
    • Journal of the Korean Physical Society
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    • 제73권9호
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    • pp.1219-1224
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    • 2018
  • We investigate the evolutionary dynamics and the phase transitions of the island model which consists of subdivided populations of individuals confined to two islands. In the island model, the population is subdivided so that migration acts to determine the evolutionary dynamics along with selection and genetic drift. The individuals are assumed to be haploid and to be one of two species, X or Y. They reproduce according to their fitness values, die at random, and migrate between the islands. The evolutionary dynamics of an individual based model is formulated in terms of a master equation and is approximated by using the diffusion method as the multidimensional Fokker-Planck equation (FPE) and the coupled non-linear stochastic differential equations (SDEs) with multiplicative noise. We analyze the infinite population limit to find the phase transitions from the monomorphic state of one type to the polymorphic state to the monomorphic state of the other type as we vary the ratio of the fitness values in two islands and complete the phase diagram of our island model.

전기철도차량 경제운전 모형 개발 (Development of Economical Run Model for Electric Railway Vehicle)

  • 이태형;황희수
    • 한국철도학회논문집
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    • 제9권1호
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    • pp.76-80
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    • 2006
  • The Optimization has been performed to search an economical running pattern in the view point of trip time and energy consumption. Fuzzy control model have been applied to build the meta-model. To identify the structure and its parameters of a fuzzy model, fuzzy c-means clustering method and differential evolutionary scheme are utilized, respectively. As a result, two meta-models for trip time and energy consumption were constructed. The optimization to search an economical running pattern was achieved by differential evolutionary scheme. The result shows that the proposed methodology is very efficient and conveniently applicable to the operation of railway system.

한국형 고속열차 경계운전 모형 개발 (Development of Economical Run Model for High Speed Rolling stock 350 experimental)

  • 이태형;박춘수
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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    • pp.238-240
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    • 2005
  • The Optimization has been performed to search an economical running pattern in the view point of trip time and energy consumption. Fuzzy control model have been applied to build the meta-model. To identify the structure and its parameters of a fuzzy model, fuzzy c-means clustering method and differential evolutionary scheme are utilized, respectively. As a result, two meta-models for trip time and energy consumption were constructed. The optimization to search an economical running pattern was achieved by differential evolutionary scheme. The result shows that the proposed methodology is very efficient and conveniently applicable to the operation of railway system.

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