• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2702-2719
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• 2013

A new optimal scheme based on curvelet transform is proposed for retinal image enhancement (RIE) using real-coded quantum genetic algorithm. Curvelet transform has better performance in representing edges than classical wavelet transform for its anisotropy and directional decomposition capabilities. For more precise reconstruction and better visualization, curvelet coefficients in corresponding subbands are modified by using a nonlinear enhancement mapping function. An automatic method is presented for selecting optimal parameter settings of the nonlinear mapping function via quantum genetic search strategy. The performance measures used in this paper provide some quantitative comparison among different RIE methods. The proposed method is tested on the DRIVE and STARE retinal databases and compared with some popular image enhancement methods. The experimental results demonstrate that proposed method can provide superior enhanced retinal image in terms of several image quantitative evaluation indexes.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.43-51
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• 2022

In this paper, we suggest the method to improve the existing method leaning context-free grammar(CFG) using tabular representation(TBL) as a chromosome of genetic algorithm in grammatical inference and show the more efficient experimental result. We have two improvements. The first is to improve the formula to reflect the learning evaluation of positive and negative examples at the same time for the fitness function. The second is to classify partitions corresponding to TBLs generated from positive learning examples according to the size of the learning string, proceed with the evolution process by class, and adjust the composition ratio according to the success rate to apply the learning method linked to survival in the next generation. These improvements provide better efficiency than the existing method by solving the complexity and difficulty in the crossover and generalization steps between several individuals according to the size of the learning examples. We experiment with the languages proposed in the existing method, and the results show a rather fast generation rate that takes fewer generations to complete learning with the same success rate than the existing method. In the future, this method can be tried for extended CYK, and furthermore, it suggests the possibility of being applied to more complex parsing tables.

• KIEAE Journal
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• v.15 no.3
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• pp.29-36
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• 2015

Purpose: This study is as only basic research for the model Development of the New-Hanok Type Service Facilities in Apartment Housing, which is as a decisive factor used as a planning element for developing the model inherited tradition, There aimed at extracting the genetic factor of Korea's traditional architecture. Method: For this purpose, Consider the concept and regulations of the New-Hanok Type Service Facilities in Apartment Housing and examined the Domestic Application Status of the New-Hanok Type Service Facilities in Apartment Housing. It sets direction of the New-Hanok Type models development based on Expert advice and the literature, and was reviewed a primal reason system of Korea as an extraction base of genetic factors. Result: Then Through the framework of the vertical axis (the form), the horizontal axis (space), It extracted the genetic factors of the Korea Traditional Architecture, classified the genetic factors extracted as the structure(layout, construction, space), features, traditional beauty, investigated the content of the form representation and spatial meaning, and were characterized. Based on the result, It were comprehensive the genetic factors extracted as plan Elements for inheriting of the traditions.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1161-1164
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• 1996

In this paper, a parameter optimization technique for a mobile robot navigation is discussed. Authors already have proposed a navigation algorithm for mobile robots with sonar sensors using fuzzy decision making theory. Fuzzy decision making selects the optimal via-point utilizing membership values of each via-point candidate for fuzzy navigation goals. However, to make a robot successfully navigate through an unknown and cluttered environment, one needs to adjust parameters of membership function, thus changing shape of MF, for each fuzzy goal. Furthermore, the change in robot configuration, like change in sensor arrangement or sensing range, invokes another adjusting of MFs. To accomplish an intelligent way to adjust these parameters, we adopted a genetic algorithm, which does not require any formulation of the problem, thus more appropriate for robot navigation. Genetic algorithm generates the fittest parameter set through crossover and mutation operation of its string representation. The fitness of a parameter set is assigned after a simulation run according to its time of travel, accumulated heading angle change and collision. A series of simulations for several different environments is carried out to verify the proposed method. The results show the optimal parameters can be acquired with this method.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.79-87
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• 2023

In this paper, we propose a novel genetic algorithm to reduce the overall span time by optimizing the skid insertion sequence in the shipyard subassembly process. We represented a solution by a permutation of a set of skid ids and applied genetic operators suitable for such a representation. In addition, we combined the genetic algorithm and the existing heuristic algorithm called UniDev which is properly modified to improve the search performance. In particular, the slow skid search part in UniDev was changed to a greedy algorithm. Through extensive large-scaled simulations, it was observed that the span time of our method was stably minimized compared to Multi-Start search and a genetic algorithm combined with UniDev.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.809-812
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• 2008

통신 시스템에 대한 관심은 인터넷의 급격한 발전에 의해 가상공간의 출현과 유비쿼터스 컴퓨팅 환경 구축에 대한 요구가 증대됨에 따라 관련 이론 및 기술의 발전을 주도해 왔다. 이와 관련하여 가장 근간이 되는 문제들 중 하나는 최적 정보 통신 스패닝 트리 (OCST: Optimal Communication Spanning Tree) 설계 문제이다. 본 논문에서는 이러한 OCST 설계 문제를 네트워크 신뢰도를 고려하여 해결하기 위해 유전 알고리즘 (GA)를 이용한다. 본 논문에서는 유전 알고리즘을 이용함에 있어서 n개의 노드들로 구성된 네트워크 문제에서 n-2개의 숫자열로 표현 가능한 유전자 표현법을 이용하고 신뢰성 있는 OCST 설계 문제 해결을 위한 해법으로서 유전 알고리즘을 제안한다. 임의로 생성된 예제에 대한 수치 실험을 통해 통신시스템의 기본 문제 중 하나인 OCST 설계 문제의 해법으로서의 제안 알고리즘의 유용성과 효율성을 확인한다.

• Journal of the Korea Safety Management & Science
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• v.5 no.1
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• pp.69-82
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• 2003

The sequence which minimizes overall utility work in car assembly lines reduces the cycle time, the number of utility workers, and the risk of conveyor stopping. This study suggests mathematical formulation of the sequencing problem to minimize overall utility work, and present a genetic algorithm which can provide a near optimal solution in real time. To apply a genetic algorithm to the sequencing problem in car assembly lines, the representation, selection methods, and genetic parameters are studied. Experiments are carried out to compare selection methods such as roullette wheel selection, tournament selection and ranking selection. Experimental results show that ranking selection method outperforms the others in solution quality, whereas tournament selection provides the best performance in computation time.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1124-1129
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• 2003

In mechanical design, design process is mainly composed of design, explanation and evaluation. In this paper, Using Genetic Algorithms (GA), Evolutionary computation is introduced as new design process. This method promote the efficiency and power of design. Due to the known characteristics of the stage, the approach basically involves a synthetic design method with the composition of building blocks representing the elements of mechanical objects. In order for the building blocks to be more suitable for representation and evolution of mechanical structures, Elementary Cell Blocks (ECBs) are introduced as new building blocks. In this paper, we have demonstrated the implementation of the approach with the design of gear systems.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.267-275
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• 2004

Directed graph and Lindenmayer system (L-system) are two major encoding methods of representation to develop creatures in application field of artificial life. It is difficult to define real morphology structurally using the L-systems which are a grammatical rewriting system because L-systems represent genotype as loops, procedure calls, variables, and parameters. This paper defines a class of representations called structured directed graph, which is identified by its ability to define structures of the genotype in the translation to the phenotype, and presents an example of creating 3D flowers using a directed graph which is proper method to represent real morphology, and interactive genetic algorithm which decodes the problem with human's emotional evaluation. The experimental results show that natural flower morphology can be generated by the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.702-705
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• 2003

Directed graph and Lindenmayer system (L-system) are two major encoding methods of representation to develop creatures in an application field of artificial life. It is difficult to structurally define real morphology using the L-systems which are a grammatical rewriting system because they represent genotype as loops, procedure calls, variables, and parameters. This paper defines a class of representations called structured directed graph and interactive genetic algorithm for automatically creating 3D flower morphology. The experimental results show that natural flower morphology can be created by the proposed method.