• Journal of electromagnetic engineering and science
• /
• 제4권1호
• /
• pp.1-7
• /
• 2004

In this paper the Individual tap - Least Mean Square(IT-LMS) algorithm is applied to the adaptive multipath channel equalization using hybrid-type Genetic Algorithm(GA) for achieving lower minimum Mean Squared Error(MSE). Owing to the global search performance of GA, LMS-type equalizers combined with it have shown preferable performance in both global and local search but those still have unsatisfying minimum MSE performance. In order to lower the minimum MSE we investigated excess MSE of IT-LMS algorithm and applied it to the hybrid GA equalizer. The high convergence rate and lower minimum MSE of the proposed system give us reason to expect that it will perform well in practical multi-path channel equalization systems.

• 한국컴퓨터정보학회논문지
• /
• 제11권6호
• /
• pp.79-86
• /
• 2006

영상 식별 기술은 대용량의 멀티미디어 데이터베이스 환경 하에서 고속의 검색을 위해서 필수적이다. 본 논문은 이러한 고속 검색을 위하여 GA(Genetic Algorithm)과 SVM(Support Vector Machine)을 결합한 모델을 제안한다. 특징벡터로는 색상 정보와 질감 정보를 사용하였다. 이렇게 추출된 특징벡터의 집합을 제안한 모델을 통해 최적의 유효 특징벡터의 집합를 찾아 영상을 식별하여 정확도를 높였다. 성능평가는 색상, 질감. 색상과 질감의 연합 특징벡터를 각각 사용한 성능 비교. SYM과 제안된 알고리즘과의 성능을 비교하였다. 실험 결과 색상과 질감을 연합한 특징벡터를 사용한 것이 단일 특징벡터를 사용한 것 보다 좋은 결과를 보였으며 하이브리드 기법을 이용한 제안된 알고리즘이 SVM알고리즘만을 이용한 것 보다 좋은 결과를 보였다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
• /
• pp.191-194
• /
• 2003

Location-allocation problem is known as one of the important problem faced in Industrial Engineering and Operations Research fielde. There are many variations on this problem for different applications, however, most of them consider no obstacle existing. Since the location-allocation problem with obstacles is very complex and with many infeasible solutions, no direct method is effective to solve it. In this paper we propose a hybrid Genetic Algorithm (hGA) method for solving this problem. The proposed hGA is based on Lagrangian relaxation method and Dijkstra's shortest path algorithm. To enhance the proposed hGA, a Fuzzy Logic Controller (FLC) approach is also adopted to auto-tune the GA parameters.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제4권3호
• /
• pp.259-265
• /
• 2004

In this study, a hybrid genetic algorithm merged with simulated annealing is presented to solve nonlinear channel blind equalization problems. The equalization of nonlinear channels is more complicated one, but it is of more practical use in real world environments. The proposed hybrid genetic algorithm with simulated annealing is used to estimate the output states of nonlinear channel, based on the Bayesian likelihood fitness function, instead of the channel parameters. By using the desired channel states derived from these estimated output states of the nonlinear channel, the Bayesian equalizer is implemented to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a conventional genetic algorithm(GA) and a simplex GA. In particular, we observe a relatively high accuracy and fast convergence of the method.

• 전기학회논문지
• /
• 제57권8호
• /
• pp.1334-1341
• /
• 2008

This paper introduces an approach of Hybrid Particle Swarm Optimization(HPSO) for a security-constrained economic dispatch(SCED) with line flow constraints. To reduce a early convergence effect of PSO algorithm, we proposed HPSO algorithm considering a mutation characteristic of Genetic Algorithm(GA). In power system, for considering N-1 line contingency, we have chosen critical line contingency through a process of Screening and Selection based on PI(performance Index). To prove the ability of the proposed HPSO in solving nonlinear optimization problems, SCED problems with nonconvex solution spaces are considered and solved with three different approach(Conventional GA, PSO, HPSO). We have applied to IEEE 118 bus system for verifying a usefulness of the proposed algorithm.

• 한국지능시스템학회논문지
• /
• 제7권4호
• /
• pp.58-64
• /
• 1997

FLC(퍼지 제어기 : Fuzzy Logic Controller)는 고전적 제어기보다 외란(disturbance)에 강하고 초기 치의 과도측성(overshoot)이 우수하다. 그리고 미지의 프로세스(process)나 복잡한 시스템의 수학적인 모델링이 불가능한 경우에도 퍼지 추론에 의하여 적절한 제어량을 얻을 수 있다. 그러나 퍼지변수의 양자화 단계 크기에 의해 출력값이 항상 미세한 오차를 가지므로 목표치에 정확히 수럼하지 못한다.[1]. 이 미세한 오차를 제거하기 위한 여러 방법이 [2~4]있지만 본 논문에서는 FLC에 GA(유전알고리즘 : Genetic Algorithm)와 EP(진화프로그래밍 : Evolution programming)를 결합한 GA-FLC, EPFLC Hybrid 제어기를 제안한다. 이 Hybrid 제어기의 츨력 특성과 FLC의 출력 특성을 비교 분석하고, 이 Hybrid 제어기가 오차없이 목표치에 잘 수렴하는 것을 보이고자 한다. 또한 이 두 종류의 Hybrid제어기 수렴 속도 성능도 비교한다.

• 한국산업정보학회논문지
• /
• 제27권1호
• /
• pp.37-48
• /
• 2022

본 연구에서는 공학설계 최적화 문제 해결을 위한 혼합 메타휴리스틱(Hybrid Meta-heuristic) 접근법을 제안된다. 공학 설계 최적화 문제는 다양한 형태의 변수를 가지며, 복잡한 제약조건들하에서 그 최적해를 구하는 문제로 이미 많은 기존 연구들을 통해 다양한 접근법들이 개발되어져 왔다. 하지만 그 효율성은 아직까지 크게 개선되지 못하고 있는 실정이다. 따라서 본 연구에서는 이러한 효율성을 개선하기 위한 새로운 접근법을 제안한다. 제안된 혼합 메타휴리스틱 접근법은 탐색 공간에 대한 전역적 탐색을 위해 유전알고리즘(Genetic Algorithm: GA) 접근법, 지역적 탐색을 위해 변동이웃탐색(Variable Neighborhood Search: VNS) 접근법과 언덕오르기(Hill Climbing: HC) 접근법을 혼합(GA-VNS-HC)하였다. 사례 연구에서는 다양한 형태의 공학설계 최적화 문제를 이용하여 본 연구에서 제안한 GA-VNS-HC 접근법의 우수성을 입증하였다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
• /
• pp.863-868
• /
• 1992

This paper presents a method on applying Genetic Algorithm(GA), which is a well-known high performance optimizing algorithm, to construct the self-organizing fuzzy logic controller. Fuzzy logic controller considered in this paper utilizes Sugeno's hybrid inference method, which has an advantage of simple defuzzification process in the inference engine. Genetic algorithm is used to find the optimal parameters in the FLC. The proposed approach will be demonstrated using 2 d.o.f robot manipulator to verify its effectiveness.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 하계학술대회 논문집 A
• /
• pp.446-448
• /
• 2004

This paper presents an application of parallel hybrid Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a service restoration in distribution system. In parallel hybrid GA-TS, after GA operations, strings which are not emerged in the past population are selected in the reproduction procedure. After reproduction operation, if there are many strings which are in the past population, we add new random strings into the population. If there's no improvement for the predetermined iteration, local search procedure is executed by f for the strings with high fitness function value. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a practical distribution system in Korea.

• Steel and Composite Structures
• /
• 제47권6호
• /
• pp.759-779
• /
• 2023

The paper proposes two hybrid metaheuristic optimization and artificial neural network (ANN) methods for the close prediction of the ultimate axial compressive capacity of concentrically loaded concrete filled double skin steel tube (CFDST) columns. Two metaheuristic optimization, namely genetic algorithm (GA) and particle swarm optimization (PSO), approaches enable the dynamic training architecture underlying an ANN model by optimizing the number and sizes of hidden layers as well as the weights and biases of the neurons, simultaneously. The former is termed as GA-ANN, and the latter as PSO-ANN. These techniques utilize the gradient-based optimization with Bayesian regularization that enhances the optimization process. The proposed GA-ANN and PSO-ANN methods construct the predictive ANNs from 125 available experimental datasets and present the superior performance over standard ANNs. Both the hybrid GA-ANN and PSO-ANN methods are encoded within a user-friendly graphical interface that can reliably map out the accurate ultimate axial compressive capacity of CFDST columns with various geometry and material parameters.