• 제목/요약/키워드: genetic mutation

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자가적응 유전자 알고리즘 프로세서의 VLSI 구현 (VLSI Implementation of Adaptive mutation rate Genetic Algorithm Processor)

  • 허인수;이주환;조민석;정덕진
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
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    • pp.157-160
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    • 2001
  • This paper has been studied a Adaptive Mutation rate Genetic Algorithm Processor. Genetic Algorithm(GA) has some control parameters such as the probability of bit mutation or the probability of crossover. These value give a priori by the designer There exists a wide variety of values for for control parameters and it is difficult to find the best choice of these values in order to optimize the behavior of a particular GA. We proposed a Adaptive mutation rate GA within a steady-state genetic algorithm in order to provide a self-adapting mutation mechanism. In this paper, the proposed a adaptive mutation rate GAP is implemented on the FPGA board with a APEX EP20K600EBC652-3 devices. The proposed a adaptive mutation rate GAP increased the speed of finding optimal solution by about 10%, and increased probability of finding the optimal solution more than the conventional GAP

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변형된 돌연변이를 가진 대화형 유전자 알고리즘을 이용한 학습 콘텐츠의 설계 및 구현 (Design and Implementation of Learning Contents Using Interactive Genetic Algorithms with Modified Mutation)

  • 김정숙
    • 한국컴퓨터정보학회논문지
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    • 제10권6호
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    • pp.85-92
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    • 2005
  • 본 논문에서는 변형된 돌연변이 연산자를 적용한 대화형 유전자 알고리즘을 사용해서 웹-기반 학습 콘텐츠를 개발하였다. 대화형 유전자 알고리즘은 주로 상호 교환(reciprocal exchange) 돌연변이를 사용한다. 그러나 본 논문에서는 학습자의 학습 효과를 높이기 위해 돌연변이 연산자를 변형하였다. 그리고, 대화형 유전자 알고리즘을 이용한 웹 기반 학습 콘텐츠는 동적인 학습 내용과 실시간 테스트 시스템을 제공한다. 특히 학습자가 자신의 특성과 흥미에 따라 대화형 유전자 알고리즘을 수행하면서 효율적인 학습 환경과 콘텐츠 배열 순서를 선택할 수 있다.

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Developing a new mutation operator to solve the RC deep beam problems by aid of genetic algorithm

  • Kaya, Mustafa
    • Computers and Concrete
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    • 제22권5호
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    • pp.493-500
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    • 2018
  • Due to the fact that the ratio of their height to their openings is very large compared to normal beams, there are difficulties in the design and analysis of deep beams, which differ in behavior. In this study, the optimum horizontal and vertical reinforcement diameters of 5 different beams were determined by using genetic algorithms (GA) due to the openness/height ratio (L/h), loading condition and the presence of spaces in the body. In this study, the effect of different mutation operators and improved double times sensitive mutation (DTM) operator on GA's performance was investigated. In the study following random mutation (RM), boundary mutation (BM), non-uniform random mutation (NRM), Makinen, Periaux and Toivanen (MPT) mutation, power mutation (PM), polynomial mutation (PNM), and developed DTM mutation operators were applied to five deep beam problems were used to determine the minimum reinforcement diameter. The fitness values obtained using developed DTM mutation operator was higher than obtained from existing mutation operators. Moreover; obtained reinforcement weight of the deep beams using the developed DTM mutation operator lower than obtained from the existing mutation operators. As a result of the analyzes, the highest fitness value was obtained from the applied double times sensitive mutation (DTM) operator. In addition, it was found that this study, which was carried out using GAs, contributed to the solution of the problems experienced in the design of deep beams.

도로선형최적화를 위한 유전자 연산자의 적용 (Incorporating Genetic Operators into Optimizing Highway Alignments)

  • 김응철
    • 대한교통학회지
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    • 제22권2호
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    • pp.43-54
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    • 2004
  • 본 연구에서는 인공지능(Artificial Intelligence)방법 중의 하나인 유전자 알고리즘(Genetic Algorithm)을 도로선형최적화 모형개발의 탐색엔진으로 활용하기 위한 핵심도구인 유전자 연산자(Genetic Operator)의 개발과 적용과정을 통해 그 특징과 유용성을 제시하였다. 균일돌연변이 연산자, 직선돌연변이 연산자. 비균일 돌연변이 연산자, 전체 비균일 돌연변이 연산자 등 4개의 돌연변이 연산자가 탐색영역(Search space)의 가능한 모든 부분을 탐험(Exploration)하기 위해 적용되었으며, 단순교차 연산자, 두 개의 점을 이용한 교차 연산자, 산술교차 연산자, 학습교차 연산자 등 4개의 교차 연산자가 노선대안의 우수한 유전형질을 다음세대에 효과적으로 전달(Exploitation)하기 위해 시험되었다. 사례연구와 민감도 분석과정을 통해 유전자 알고리즘 및 개발 적용된 8개 유전자 연산자의 도로선형최적화과정 도입이 우수한 노선대안을 빠르고 효과적으로 탐색함을 알 수 있었으며, 돌연변이 연산자와 교차 연산자의 효과적 조합이 상호보완기능을 통해 탐색능력의 향상에 큰 영향을 끼치는 것으로 파악되었다. 또한, 개발 적용된 연산자 이외에도 새로운 연산자의 개발 가능성이 무한하며, 이는 도로선형최적화에 유전자 알고리즘의 적용이 타당함을 반증함도 주목할 만하다.

병렬 유전 알고리즘 기반 meta-유전 알고리즘을 이용한 교차율과 돌연변이율의 최적화 (Optimization of Crossover and Mutation Rate Using PGA-Based meta-GA)

  • 김문환;박진배;이연우;주영훈
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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    • pp.375-378
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    • 2002
  • In this paper we propose parallel GA to optimize mutation rate and crossover rate using server-client model. The performance of GA depend on the good choice of crossover and mutation rates. Although many researcher has been study about the good choice, it is still unsolved problem. proposed GA optimize crossover and mutation rates trough evolving subpopulation. In virtue of the server-client model, these parameters can be evolved rapidly with relatively low-grade

동적인 교차 및 동연변이 확률을 갖는 균일 교차방식 유전 알고리즘 (A genetic algorithm with uniform crossover using variable crossover and mutation probabilities)

  • 김성수;우광방
    • 제어로봇시스템학회논문지
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    • 제3권1호
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    • pp.52-60
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    • 1997
  • In genetic algorithms(GA), a crossover is performed only at one or two places of a chromosome, and the fixed probabilities of crossover and mutation have been used during the entire generation. A GA with dynamic mutation is known to be superior to GAs with static mutation in performance, but so far no efficient dynamic mutation method has been presented. Accordingly in this paper, a GA is proposed to perform a uniform crossover based on the nucleotide(NU) concept, where DNA and RNA consist of NUs and also a concrete way to vary the probabilities of crossover and mutation dynamically for every generation is proposed. The efficacy of the proposed GA is demonstrated by its application to the unimodal, multimodal and nonlinear control problems, respectively. Simulation results show that in the convergence speed to the optimal value, the proposed GA was superior to existing ones, and the performance of GAs with varying probabilities of the crossover and the mutation improved as compared to GAs with fixed probabilities of the crossover and mutation. And it also shows that the NUs function as the building blocks and so the improvement of the proposed algorithm is supported by the building block hypothesis.

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Genetic improvement of potato plants

  • Suharsono, Sony
    • 한국작물학회:학술대회논문집
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    • 한국작물학회 2017년도 9th Asian Crop Science Association conference
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    • pp.12-12
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    • 2017
  • Genetic improvement in potato can be carried out through several approaches, as sexual crosses, somatic hybridization, mutation and genetic engineering. Although the approach is different, but the goal is the same, to get a superior cultivar. Mutation and genetic engineering are very interesting methods for genetic improvement of potato plants. Mutation by gamma-ray irradiation have been performed to get some new potato cultivars which are more resistant to disease and have higher productivity. We have carried out a mutation of some potato cultivars and obtained some excellent clones to be potentially released as new superior cultivars. By the mutation method, we have released one potato cultivar for the French fries industry, and we registered one cultivar of potato for chips, and two cultivar for vegetable potatoes. Actually we are doing multi-location trial for three clones to be released as new cultivars. Through genetic engineering, several genes have been introduced into the potato plant, and we obtained several clones of transgenic potato plants. Transgenic potato plants containing FBPase gene encoding for fructose bisphosphatase, have a higher rate of photosynthesis and higher tuber productivity than non-transgenic plants. This result suggests that FBPase plays an important role in increasing the rate of photosynthesis and potato tuber productivity. Some transgenic potatoes containing the Hd3a gene are currently being evaluated for their productivity. Over expression of the Hd3a gene is expected to increase tuber productivity and induce flowering in potatoes. Transgenic potato plants containing MmPMA gene encoding for plasma membrane ATPse are more tolerant to low pH than non-transgenic plants, indicating that plasma membrane ATPase plays an important role in the potato plant tolerance to low pH stress. Transgenic potato plants containing c-lysozyme genes, are highly tolerant of bacterial wilt diseases caused by Ralstonia solanacearum and bacterial soft rot disease caused by Pectobacterium carotovorum. Expression of c-lyzozyme gene plays an important role in increasing the resistance of potato plants to bacterial diseases.

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Multimodal Optimization Based on Global and Local Mutation Operators

  • Jo, Yong-Gun;Lee, Hong-Gi;Sim, Kwee-Bo;Kang, Hoon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1283-1286
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    • 2005
  • Multimodal optimization is one of the most interesting topics in evolutionary computational discipline. Simple genetic algorithm, a basic and good-performance genetic algorithm, shows bad performance on multimodal problems, taking long generation time to obtain the optimum, converging on the local extrema in early generation. In this paper, we propose a new genetic algorithm with two new genetic mutational operators, i.e. global and local mutation operators, and no genetic crossover. The proposed algorithm is similar to Simple GA and the two genetic operators are as simple as the conventional mutation. They just mutate the genes from left or right end of a chromosome till the randomly selected gene is replaced. In fact, two operators are identical with each other except for the direction where they are applied. Their roles of shaking the population (global searching) and fine tuning (local searching) make the diversity of the individuals being maintained through the entire generation. The proposed algorithm is, therefore, robust and powerful.

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구륜 이동 로보트의 경로 추적을 위한 Fuzzy-Genetic Controller 설계 (Design fuzzy-genetic controller for path tracking in wheeled-mobile robot)

  • 김상원;김성희;박종국
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.512-515
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    • 1997
  • In this paper the fuzzy-genetic controller for path-tracking of WMRs is proposed. Fuzzy controller is implemented to adaptive adjust the crossover rate and mutation rate, and genetic algorithm is implemented to adaptive adjust the control gain during the optimization. The computer simulation shows that the proposed fuzzy-genetic controller is effective.

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Colon Cancer Prevention by Detection of APC Gene Mutation in a Family with Attenuated Familial Adenomatous Polyposis

  • Poovorawan, Kittiyod;Suksawatamnuay, Sirinporn;Sahakitrungruang, Chucheep;Treeprasertsuk, Sombat;Wisedopas, Naruemon;Komolmit, Piyawat;Poovorawan, Yong
    • Asian Pacific Journal of Cancer Prevention
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    • 제13권10호
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    • pp.5101-5104
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    • 2012
  • Background: Genetic mutation is a significant factor in colon CA pathogenesis. Familial adenomatous polyposis (FAP) is an autosomal dominant hereditary disease characterized by multiple colorectal adenomatous polyps affecting a number of cases in the family. This report focuses on a family with attenuated familial adenomatous polyposis (AFAP) with exon 4 mutation, c.481C>T p.Q161X of the APC gene. Methods: We analyzed 20 members of a family with AFAP. Clinical and endoscopic data were collected for phenotype determination. Genetic analysis was also performed by direct sequencing of the APC gene. Result: Five patients with a phenotype of AFAP were found. Endoscopic polyposis was demonstrated among the second generation with genotype mutation of the disease (age > 50 years) consistent with delayed phenotypic adenomatous polyposis in AFAP. APC gene mutation was identified in exon 4 of the APC gene, with mutation points of c.481C>T p.Q161X. Laparoscopic subtotal colectomy was performed to prevent carcinogenesis. Conclusion: A family with attenuated familial adenomatous polyposis of APC related to exon 4 mutation, c.481C>T p.Q161X, was reported and the phenotypic finding was confirmed by endoscopic examination. Genetic mutation analysis might be advantageous in AFAP for long term colon cancer prevention and management due to subtle or asymptomatic phenotype presentation in early adulthood.