• 제목/요약/키워드: genetically optimized

검색결과 49건 처리시간 0.025초

진화론적으로 최적화된 Context-based RBF 뉴럴 네트워크 설계 (Design of Genetically Optimized Context-based RBFNN)

  • 박호성;오성권;김현기
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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    • pp.258-260
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    • 2009
  • 본 논문에서는 최적화 알고리즘인 유전자 알고리즘과 context-based FCM 클러스터링 방법을 이용하여 새로운 형태의 RBF 뉴럴 네트워크의 포괄적인 설계 방법론을 소개한다. 제안된 구조는 클러스터링 기법을 기반하여 사용된 데이터의 특성에 효과적인 모델을 구축하고자 한다. 또한 유전자 알고리즘을 이용하여 모델의 최적화에 주요한 영향을 미치는 파리미터들(-은닉층에서의 contex의 수, contex에 포괄되는 노드의 수, 그리고 contex에 입력되는 입력변수)을 동조한다. 제안된 모델의 설계 공정은 1) K-means 클러스터링을 통한 context fuzzy set에 대한 정의와 설계, 2) context-based fuzzy clustering에 대한 모델의 적용과 이에 따른 모델 구축의 효율성, 3) 유전자 알고리즘을 통한 모델 최적화를 위한 파라미터들의 최적화와 같은 단계로 구성되어 있다. 구축된 RBF 뉴럴 네트워크의 후반부 다항식에 대한 parameter들은 성능지수를 최소화하기 위해 Least Square Method에 의해서 보정된다. 본 논문에서는 모델을 설계함에 있어서 체계적인 설계 알고리즘을 포괄적으로 설명하고 있으며, 더 나아가 제안된 모델의 성능을 다른 표준적인 모델들과 대조함으로써 제안된 모델의 우수성을 나타내고자 한다.

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HVDC 시스템을 위한 진화론적으로 최적화된 자기 동조 퍼지제어기 (Genetically optimized self-tuning Fuzzy-PI controller for HVDC system)

  • 왕중선;양정제;안태천
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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    • pp.279-281
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    • 2006
  • In this paper, we study an approach to design a self-tuning Fuzzy-PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of conversional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. The above problems are solved by adapting Fuzzy-PI controller for the fire angle control of rectifier.[7] The performance of the Fuzzy-PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain the optimal scaling factors of the Fuzzy-PI controller by Genetic Algorithms. In order to improve Fuzzy-PI controller, we adopt FIS to tune the scaling factors of the Fuzzy-PI controller on line. A comparative study has been performed between Fuzzy-PI and self-tuning Fuzzy-PI controller, to prove the superiority of the proposed scheme.

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부분방전 패턴인식을 위한 퍼지뉴럴네트워크의 유전자적 최적 설계 (Genetically Optimized Design of Fuzzy Neural Networks for Partial Discharge Pattern Recognition)

  • 박건준;김길성;오성권;최원;김정태
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 제39회 하계학술대회
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    • pp.1891-1892
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    • 2008
  • 본 논문에서는 부분방전 패턴인식을 위한 퍼지뉴럴네크워크(Fuzzy-Nueral Network를 설계한다. 퍼지뉴럴네트워크의 구조에서 규칙의 전반부는 개별적인 입력 공간을 분할하여 표현하고, 규칙의 후반부는 다항식으로서 표현되며 오류역전파 알고리즘을 이용하여 연결가중치인 후반부 다항식의 계수를 학습한다. 또한, 유전자 알고리즘을 이용하여 각 입력에 대한 전반부 멤버쉽함수의 정점과 학습률 및 모멤텀 계수를 최적으로 동조한다. 제안된 네트워크는 부분방전 패턴인식을 위해 다중 출력을 가지며, 초고압 XLPE 케이블 절연접속함의 모의결함에 대해 부분방전 신호를 패턴인식한다. 부분방전 신호는 PRPDA 방법을 통해 256개의 입력 벡터와 4개의 출력 벡터를 가지며, 보이드 방전, 코로나 방전, 표면 방전, 노이즈의 4개 클래스를 분류하며, 패턴인식률로서 결과를 분석한다.

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Ni-Ti actuators and genetically optimized compliant ribs for an adaptive wing

  • Mirone, Giuseppe
    • Smart Structures and Systems
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    • 제5권6호
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    • pp.645-662
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    • 2009
  • Adaptive wings are capable of properly modifying their shape depending on the current aerodynamic conditions, in order to improve the overall performance of a flying vehicle. In this paper is presented the concept design of a small-scale compliant wing rib whose outline may be distorted in order to switch from an aerodynamic profile to another. The distortion loads are induced by shape memory alloy actuators placed within the frame of a wing section whose elastic response is predicted by the matrix method with beam formulation. Genetic optimization is used to find a wing rib structure (corresponding to the first airfoil) able to properly deforms itself when loaded by the SMA-induced forces, becoming as close as possible to the desired target shape (second airfoil). An experimental validation of the design procedure is also carried out with reference to a simplified structure layout.

Evolutionary Data Granulation 기반으로한 퍼지 집합 다항식 뉴럴 네트워크에 관한 연구 (A Study on Fuzzy Set-based Polynomial Neural Networks Based on Evolutionary Data Granulation)

  • 노석범;안태천;오성권
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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    • pp.433-436
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    • 2004
  • In this paper, we introduce a new Fuzzy Polynomial Neural Networks (FPNNS)-like structure whose neuron is based on the Fuzzy Set-based Fuzzy Inference System (FS-FIS) and is different from that of FPNNS based on the Fuzzy relation-based Fuzzy Inference System (FR-FIS) and discuss the ability of the new FPNNS-like structure named Fuzzy Set-based Polynomial Neural Networks (FSPNN). The premise parts of their fuzzy rules are not identical, while the consequent parts of the both Networks (such as FPNN and FSPNN) are identical. This difference results from the angle of a viewpoint of partition of input space of system. In other word, from a point of view of FS-FIS, the input variables are mutually independent under input space of system, while from a viewpoint of FR-FIS they are related each other. The proposed design procedure for networks architecture involves the selection of appropriate nodes with specific local characteristics such as the number of input variables, the order of the polynomial that is constant, linear, quadratic, or modified quadratic functions being viewed as the consequent part of fuzzy rules, and a collection of the specific subset of input variables. On the parameter optimization phase, we adopt Information Granulation (IC) based on HCM clustering algorithm and a standard least square method-based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized FSPNN (gFSPNN), the model is experimented with using the time series dataset of gas furnace process.

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Optimization of In Vitro Murine Embryo Culture Condition based on Commercial M16 Media

  • Lee, Soo Jin;Bae, Hee Sook;Koo, Ok Jae
    • 한국수정란이식학회지
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    • 제30권4호
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    • pp.315-317
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    • 2015
  • In vitro culture of murine embryos is an important step for in vitro production systems including in vitro fertilization and generations of genetically engineered mice. M16 is widely used commercialized culture media for the murine embryos. Compared to other media such as potassium simplex optimization medium, commercial M16 (Sigma) media lacks of amino acid, glutamine and antibiotics. In the present study, we optimized M16 based embryo culture system using commercialized antibiotics-glutamine or amino acids supplements. In vivo derived murine zygote were M16 media were supplemented with commercial Penicillin-Streptomycin-Glutamine solution (PSG; Gibco) or MEM Non-Essential Amino Acids solution (NEAA; Gibco) as experimental design. Addition of PSG did not improved cleavage and blastocyst rates. On the other hand, cleavage rate is not different between control and NEAA treated group, however, blastocyst formation is significantly (P<0.05) improved in NEAA treated group. Developmental competence between PSG and NEAA treated groups were also compared. Between two groups, cleavage rate was similar. However, blastocyst formation rate is significantly improved in NEAA treated group. Taken together, beneficial effect of NEAA on murine embryos development was confirmed. Effect of antibiotics and glutamine addition to M16 media is still not clear in the study.

A Design of Dynamically Simultaneous Search GA-based Fuzzy Neural Networks: Comparative Analysis and Interpretation

  • Park, Byoung-Jun;Kim, Wook-Dong;Oh, Sung-Kwun
    • Journal of Electrical Engineering and Technology
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    • 제8권3호
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    • pp.621-632
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    • 2013
  • In this paper, we introduce advanced architectures of genetically-oriented Fuzzy Neural Networks (FNNs) based on fuzzy set and fuzzy relation and discuss a comprehensive design methodology. The proposed FNNs are based on 'if-then' rule-based networks with the extended structure of the premise and the consequence parts of the fuzzy rules. We consider two types of the FNNs topologies, called here FSNN and FRNN, depending upon the usage of inputs in the premise of fuzzy rules. Three different type of polynomials function (namely, constant, linear, and quadratic) are used to construct the consequence of the rules. In order to improve the accuracy of FNNs, the structure and the parameters are optimized by making use of genetic algorithms (GAs). We enhance the search capabilities of the GAs by introducing the dynamic variants of genetic optimization. It fully exploits the processing capabilities of the FNNs by supporting their structural and parametric optimization. To evaluate the performance of the proposed FNNs, we exploit a suite of several representative numerical examples and its experimental results are compared with those reported in the previous studies.

Optimized Culture Conditions for Production of the chimaeric protein, Uropathogenic Escherichia coli Adhesin - Cholera Toxin A2B Subunits, in Escherichia coli TB1

  • Lee, Yong-Hwa;Kim, Byung-Oh;Rhee, Dong-Kwon;Pyo, Suh-Kneung
    • Biomolecules & Therapeutics
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    • 제12권3호
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    • pp.179-184
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    • 2004
  • The FimH subunit of type 1-fimbriated Escherichia coli has been determined as a major cause for urinary tract infections. In our previous study, the Adhesin/CTXA2B was expressed as soluble recombinant chimaeric protein derived from the uropathogenic Escherichia coli adhesin genetically coupled to cholera toxin A2B (CTXA2B) subunit in Escherichia coli. Since it is very important to optimize IPTG concentration and culture temperature to maximize cell growth and productivity, These optimal culture factors were determined to increase the productivity of the expressed Adhesin/CTXA2B chimaeric protein in Escherichia coli TB1 carrying pMALfimH/ctxa2b. Our data demonstrate that optimal concentration of IPTG for increased production of chimaeric protein was 0.5 mM. Additionally, culture time was 10 hours and temperature, 37${\circ}C$.

Structural damage identification based on genetically trained ANNs in beams

  • Li, Peng-Hui;Zhu, Hong-Ping;Luo, Hui;Weng, Shun
    • Smart Structures and Systems
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    • 제15권1호
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    • pp.227-244
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    • 2015
  • This study develops a two stage procedure to identify the structural damage based on the optimized artificial neural networks. Initially, the modal strain energy index (MSEI) is established to extract the damaged elements and to reduce the computational time. Then the genetic algorithm (GA) and artificial neural networks (ANNs) are combined to detect the damage severity. The input of the network is modal strain energy index and the output is the flexural stiffness of the beam elements. The principal component analysis (PCA) is utilized to reduce the input variants of the neural network. By using the genetic algorithm to optimize the parameters, the ANNs can significantly improve the accuracy and convergence of the damage identification. The influence of noise on damage identification results is also studied. The simulation and experiment on beam structures shows that the adaptive parameter selection neural network can identify the damage location and severity of beam structures with high accuracy.

Effective Platform for the Production of Recombinant Outer Membrane Vesicles in Gram-Negative Bacteria

  • Kunjantarachot, Anthicha;Phanaksri, Teva
    • Journal of Microbiology and Biotechnology
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    • 제32권5호
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    • pp.621-629
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    • 2022
  • Bacterial outer membrane vesicles (OMVs) typically contain multiple immunogenic molecules that include antigenic proteins, making them good candidates for vaccine development. In animal models, vaccination with OMVs has been shown to confer protective immune responses against many bacterial diseases. It is possible to genetically introduce heterologous protein antigens to the bacterial host that can then be produced and relocated to reside within the OMVs by means of the host secretion mechanisms. Accordingly, in this study we sought to develop a novel platform for recombinant OMV (rOMV) production in the widely used bacterial expression host species, Escherichia coli. Three different lipoprotein signal peptides including their Lol signals and tether sequences-from Neisseria meningitidis fHbp, Leptospira interrogans LipL32, and Campylobactor jejuni JlpA-were combined upstream to the GFPmut2 model protein, resulting in three recombinant plasmids. Pilot expression studies showed that the fusion between fHbp and GFPmut2 was the only promising construct; therefore, we used this construct for large-scale expression. After inducing recombinant protein expression, the nanovesicles were harvested from cell-free culture media by ultrafiltration and ultracentrifugation. Transmission electron microscopy demonstrated that the obtained rOMVs were closed, circular single-membrane particles, 20-200 nm in size. Western blotting confirmed the presence of GFPmut2 in the isolated vesicles. Collectively, although this is a non-optimized, proof-of-concept study, it demonstrates the feasibility of this platform in directing target proteins into the vesicles for OMV-based vaccine development.