• Title/Summary/Keyword: DNA 코딩 방법

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Code Optimization of DNA Computing for Travelling Salesman Problem (Travelling Salesman Problem을 위한 DNA 컴퓨팅의 코드 최적화)

  • Kim, Eun-Kyoung;Lee, Sang-Yong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2002.11a
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    • pp.323-326
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    • 2002
  • DNA 컴퓨팅은 생체 분자들이 갖는 막대한 병렬성을 이용하여 조합 최적화 문제에 적용하는 연구가 많이 시도되고 있다. 특히 TSP(Travelling Salesman Problem)는 간선에 대한 가중치 정보가 추가되어 있기 때문에 가중치를 DNA 염기 배열로 표현하기 위한 효율저인 방법들이 제시되지 않았다. 따라서 본 논문에서는 DNA 컴퓨팅에 DNA 코딩 방법을 적용하여 정점과 간선을 효율적으로 생성하고 표현된 DNA 염기 배열의 간선에 실제간을 적용하여 가중치 정보를 계산하는 ACO(Algorithm for Code Optimization)를 제안한다. DNA 코딩 방법은 변형된 유전자 알고리즘으로 DNA 기능을 유지하며, 서열의 길이를 줄일 수 있으므로 최적의 서열을 생성할 수 있는 특징을 갖는다. 실험에서 ACO를 TSP에 적용하여 Adleman의 DNA 컴퓨팅 알고리즘과 비교하였다. 그 결과 초기 문제 표현에서 우수한 적합도 값을 생성했으며, 경로의 변화에도 능동적으로 대처하여 최적의 결과를 빠르게 탐색할 수 있었다.

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Code optimization of DNA computing for Hamiltonian path problem (Hamiltonian Path Problem을 위한 DNA 컴퓨팅의 코드 최적화)

  • 김은경;이상용
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.241-243
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    • 2002
  • DNA 컴퓨팅은 생체 분자들이 갖는 막대한 병렬성을 정보 처리 기술에 적용한 기술이다. Adleman의 DNA 컴퓨팅은 랜덤한 고정길이의 형태로 문제를 표현하기 때문에 해를 찾지 못하거나 시간이 많이 걸리는 단점을 갖고 있다. 본 논문은 DNA 컴퓨팅에 DNA 코딩 방법을 적용하여 DNA 서열을 효율적으로 표현하고 반응횟수 만큼 합성과 분리 과정을 거쳐 최적의 코드를 생성하는 ACO(Algorithm for Code Optimization)를 제안한다. DNA 코딩 방법은 변형된 유전자 알고리즘으로 DNA 기능을 유지하며, 서열의 길이를 줄일 수 있으므로 최적의 서열을 생성할 수 있는 특징을 갖는다. ACO를 NP-complete 문제 중 Hamiltonian path problem에 적용하여 실험한 결과, Adleman의 DNA 컴퓨팅 보다 초기 문제 표현에서 높은 적합도 값을 갖는 서열을 생성했으며, 경로의 변화에도 능동적으로 대처하여 최적의 결과를 빠르게 탐색할 수 있었다.

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A DNA Sequence Generation Algorithm for Traveling Salesman Problem using DNA Computing with Evolution Model (DNA 컴퓨팅과 진화 모델을 이용하여 Traveling Salesman Problem를 해결하기 위한 DNA 서열 생성 알고리즘)

  • Kim, Eun-Gyeong;Lee, Sang-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.2
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    • pp.222-227
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    • 2006
  • Recently the research for Traveling Salesman Problem (TSP) using DNA computing with massive parallelism has been. However, there were difficulties in real biological experiments because the conventional method didn't reflect the precise characteristics of DNA when it express graph. Therefore, we need DNA sequence generation algorithm which can reflect DNA features and reduce biological experiment error. In this paper we proposed a DNA sequence generation algorithm that applied DNA coding method of evolution model to DNA computing. The algorithm was applied to TSP, and compared with a simple genetic algorithm. As a result, the algorithm could generate good sequences which minimize error and reduce the biologic experiment error rate.

Fuzzy Modeling Using DNA-Coded Genetic Algorithm (DNA 코드 유전화 알고리즘을 이용한 퍼지 모델링)

  • Yu, Jin-Young;Lee, Yeun-Woo;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2003.07d
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    • pp.2295-2297
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    • 2003
  • 본 논문에서는 발생모델인 DNA 코딩 기법과 진화 모델인 유전자 알고리즘을 이용한 비선형 시스템의 퍼지 모델 링에 대한 새로운 방법을 제안한다. DNA 코딩 기법은 실제 생체 분자 (bio-molecule)를 계산의 도구로 사용하는 새로운 계산 방법으로, 진화 연산과 결합하여 인공지능의 새로운 분야로 부각되고 있다. 그러나, 실제 생체 분자를 계산의 도구로 사용하기 때문에 기존의 컴퓨터에 적용하기 어렵고, 단순히 합성과 분리라는 간단한 방법으로 해를 구하기 때문에 보다 효과적인 알고리즘을 개발하여야 할 필요성이 있다. 따라서 본 논문에서는 DNA 코드 유전자 알고리즘을 제안하며, 제안된 방법은 비선형 시스템의 퍼지 모델링에 적용하였으며, 기존의 유전자 알고리즘과 비교를 통하여 그 우수성을 입증하였다.

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Global Optimum Searching Technique Using DNA Coding and Evolutionary Computing (DNA 코딩과 진화연산을 이용한 함수의 최적점 탐색방법)

  • Paek, Dong-Hwa;Kang, Hwan-Il;Kim, Kab-Il;Han, Seung-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.6
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    • pp.538-542
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    • 2001
  • DNA computing has been applied to the problem of getting an optimal soluting since Adleman's experiment. DNA computing uses strings with various length and four-type bases that makes more useful for finding a global optimal solutions of the complex multi-modal problems This paper presents DNA coding method finding optimal solution of the multi-modal function and compares the efficiency of this method with the genetic algorithms(GA). GA searches efffectively an optimal solution via the artificial evolution of individual group of binary string and DNA coding method uses DNA molecules and four-type bases denoted by the A(Ademine) C(Gytosine);G(Guanine)and T(Thymine). The selection, crossover, mutation operators are applied to both DNA coding algorithm and genetic algorithms and the comparison has been performed. The results show that the DNA based algorithm performs better than GA.

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An Evolution of Cellular Automata Neural Systems using DNA Coding Method (DNA 코딩방법을 이용한 셀룰라 오토마타 신경망의 진화)

  • Lee, Dong-Wook;Sim, Kwee-Bo
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.12
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    • pp.10-19
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    • 1999
  • Cellular Automata Neural Systems(CANS) are neural networks based on biological development and evolution. Each neuron of CANS has local connection and acts as a form of pulse according to the dynamics of the chaotic neuron. CANS are generated from initial cells according to the CA rule. In the previous study, to obtain the useful ability of CANS, we make the pattern of initial cells evolve. However, it is impossible to represent all solution space, so we propose an evolving method of CA rule to overcome this defect in this paper. DNA coding has the redundancy and overlapping of gene and is apt for the representation of the rule. In this paper, we show the general expression of CA rule and propose translation method from DNA code to CA rule. The effectiveness of the proposed scheme was verified by applying it to the navigation problem of autonomous mobile robot.

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Performance Comparison on Pattern Recognition Between DNA Coding Method and GA Coding Method (DNA 코딩방법과 GA 코딩방법의 패턴인식 성능 비교에 관한 연구)

  • 백동화;한승수
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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    • pp.383-386
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    • 2002
  • In this paper, we investigated the pattern recognition performance of the numeric patterns (from 0 to 9) using DNA coding method. The pattern recognition performance of the DNA coding method is compared to the that of the GA(Genetic Algorithm). GA searches effectively an optimal solution via the artificial evolution of individual group of binary string using binary coding, while DNA coding method uses four-type bases denoted by A(Adenine), C(Cytosine), G(Guanine) and T(Thymine), The pattern recognition performance of GA and DNA coding method is evaluated by using the same genetic operators(crossover and mutation) and the crossover probability and mutation probability are set the same value to the both methods. The DNA coding method has better characteristics over genetic algorithms (GA). The reasons for this outstanding performance is multiple possible solution presentation in one string and variable solution string length.

Review and Suggestions for Applying DNA Sequencing to Zooplankton Researches: from Taxonomic Approaches to Biological Interaction Analysis (동물플랑크톤 연구에 있어 DNA 분석 기법의 활용 방법과 과제: 개체 동정에서 군집 분석, 생물학적 상호작용 분석까지)

  • Oh, Hye-Ji;Chae, Yeon-Ji;Choi, Yerim;Ku, Doyeong;Heo, Yu-Ji;Kwak, Ihn-Sil;Jo, Hyunbin;Park, Young-Seuk;Chang, Kwang-Hyeon;Kim, Hyun-Woo
    • Korean Journal of Ecology and Environment
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    • v.54 no.3
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    • pp.156-169
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    • 2021
  • Traditional morphological identification difficulties, such as phenotypic plasticity, misidentification of cryptic species, and larval stage species, can be compensated for by using DNA analysis techniques, such as DNA barcoding, in surveying zooplankton populations, including species identification. Recently, the rapid development of DNA sequencing techniques has allowed DNA-based community analysis not only for zooplankton assemblages in various aquatic ecosystems but also for the gut contents of zooplankton that are limited by conventional methods such as visual and microscopic identification. Therefore, the application of DNA sequencing can help understand biological interactions through the analysis of zooplankton food sources. The present paper introduces the major DNA-based approaches in zooplankton research topics, including taxonomic approaches by DNA barcoding, community-level approaches by metabarcoding, and gut content analyses, summarizes the analysis methods, and finally suggests the methodological topics that need to be considered for future applications.

Code Optimization in DNA Computing for the Hamiltonian Path Problem (해밀톤 경로 문제를 위한 DNA 컴퓨팅에서 코드 최적화)

  • 김은경;이상용
    • Journal of KIISE:Software and Applications
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    • v.31 no.4
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    • pp.387-393
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    • 2004
  • DNA computing is technology that applies immense parallel castle of living body molecules into information processing technology, and has used to solve NP-complete problems. However, there are problems which do not look for solutions and take much time when only DNA computing technology solves NP-complete problems. In this paper we proposed an algorithm called ACO(Algorithm for Code Optimization) that can efficiently express DNA sequence and create good codes through composition and separation processes as many as the numbers of reaction by DNA coding method. Also, we applied ACO to Hamiltonian path problem of NP-complete problems. As a result, ACO could express DNA codes of variable lengths more efficiently than Adleman's DNA computing algorithm could. In addition, compared to Adleman's DNA computing algorithm, ACO could reduce search time and biological error rate by 50% and could search for accurate paths in a short time.

Automatic Acquisition of Local Fuzzy Rules by DNA Coding in new Composition Reasoning Method (새로운 합성 추론법에서 DNA 코딩을 이용한 국소 퍼지 규칙의 자동획득)

  • 박종규;안태천;윤양웅
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.13 no.4
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    • pp.56-67
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    • 1999
  • In this paper, the new composition Irethod of global and local fuzzy reasoning concepts is proposed to reduce, optimize and automatically acquire the number of rules, without any lose of the general performances in conventional fuzzy controllers. In order to control the interaction between global reasoning and local reasoning, the DNA coding algorithm is introduced to the local fuzzy reasoning of the proposed composition fuzzy reasoning rrethod. The method is awlied to the real liquid level control system for the purpose of evaluating the performance. The sinru1ation results show that the proposed technique can control the system with higher accuracy and automatical1y acquire the fuzzy rules with rmre feasibility, than the conventional methods.ethods.

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