• Title/Summary/Keyword: 유전적프로그래밍

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Decision Supprot System fr Arrival/Departure of Ships in Port by using Enhanced Genetic Programming (개선된 유전적 프로그래밍 기법을 이용한 선박 입출항 의사결정 지원 시스템)

  • Lee, Kyung-Ho;Yeun, Yun-Seog;Rhee, Wook
    • Journal of Intelligence and Information Systems
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    • v.7 no.2
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    • pp.117-127
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    • 2001
  • The Main object of this research is directed to LG Oil company harbor in kwangyang-hang, where various ships ranging from 300 ton to 48000ton DWT use seven berths in the harbor. This harbor suffered from inefficient and unsafe management procedures since it is difficult to set guidelines for arrival and departure of ships according to the weather conditions and the current guidelines dose not offer clear basis of its implications. Therefore, it has long been suggested that these guidelines should be improved. This paper proposes a decision-support system, which can quantitatively decide the possibility of entry or departure on a harbor by analyzing the weather conditions (wind, current, and wave) and taking account of factors such as harbor characteristics, ship characteristics, weight condition, and operator characteristics. This system has been verified using 5$_{th}$ and 7$_{th}$ berth in Kwangyang-hang harbor. Machine learning technique using genetic programming(GP) is introduced to the system to quantitatively decide and produce results about the possibility of entry or arrival, and weighted linear associative memory (WLAM) method is also used to reduce the amount of calculation the GP has to perform. Group of additive genetic programming trees (GAGPT) is also used to improve learning performance by making it easy to find global optimum.mum.

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Genetic Programming with Weighted Linear Associative Memories and its Application to Engineering Problems (가중 선형 연상기억을 채용한 유전적 프로그래밍과 그 공학적 응용)

  • 연윤석
    • Korean Journal of Computational Design and Engineering
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    • v.3 no.1
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    • pp.57-67
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    • 1998
  • Genetic programming (GP) is an extension of a genetic algoriths paradigm, deals with tree structures representing computer programs as individuals. In recent, there have been many research activities on applications of GP to various engineering problems including system identification, data mining, function approximation, and so forth. However, standard GP suffers from the lack of the estimation techniques for numerical parameters of the GP tree that is an essential element in treating various engineering applications involving real-valued function approximations. Unlike the other research activities, where nonlinear optimization methods are employed, I adopt the use of a weighted linear associative memory for estimation of these parameters under GP algorithm. This approach can significantly reduce computational cost while the reasonable accurate value for parameters can be obtained. Due to the fact that the GP algorithm is likely to fall into a local minimum, the GP algorithm often fails to generate the tree with the desired accuracy. This motivates to devise a group of additive genetic programming trees (GAGPT) which consists of a primary tree and a set of auxiliary trees. The output of the GAGPT is the summation of outputs of the primary tree and all auxiliary trees. The addition of auxiliary trees makes it possible to improve both the teaming and generalization capability of the GAGPT, since the auxiliary tree evolves toward refining the quality of the GAGPT by optimizing its fitness function. The effectiveness of this approach is verified by applying the GAGPT to the estimation of the principal dimensions of bulk cargo ships and engine torque of the passenger car.

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Up-regulation of Pluripotency-related Genes in Human Amniotic Fluid-derived Stem Cells by ESRRB Conjugated with Cell-Penetrating Peptide (인간 양수 유래 줄기세포에서 세포투과단백질을 이용한 ESRRB 단백질의 직접도입에 의한 전분화능 관련 유전자의 발현 조절)

  • Jo, Jung-Hyun;Lee, Yu-Sun;Oh, Mi-Hee;Ko, Jung-Jae;Cheon, Yong-Pil;Lee, Dong-Ryul
    • Development and Reproduction
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    • v.14 no.4
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    • pp.243-251
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    • 2010
  • ESRRB (Estrogen related receptor $\beta$) is an orphan receptor, and have a role on maintaining the undifferentiated state and self-renewal of pluripotent stem cell as a transcription factor which regulates the expression of OCT4 and NANOG genes. Also, Feng et al. (2009) reported that Esrrb, Oct4 and Sox2 could induce pluripotent stem cell from somatic cells. The aim of the present study was to develop the direct delivery system of human ESRRB protein into human amniotic fluid-derived stem cells (AFSCs) and to analyze the effect of ESRRB on the regulation of pluripotency-related genes. Human ESRRB has three isoforms arisen by alternative splicing. We cloned short-form ESRRB and made a fusion protein of ESRRB and R7 for an efficient protein transfer to cell. R7 as cell-penetrating peptide(CPP) can help to transfer ESRRB into cells. R7-ESRRB-His6 protein was observed in the cytoplasm and nuclei within 5 hours after treatment. Also, we could observe R7-ESRRB-His6 protein only in the nuclei within 24 hours. Realtime PCR showed that ESRRB increased expression of OCT4 and NANOG as well as SOX2 gene. Therefore, we demonstrated that R7-ESRRB-His6 proteins were efficiently transferred into the nuclei of AFSCs and work well as a possible transcription factor.

Development of Decision Support System for the Design of Steel Frame Structure (강 프레임 구조물 설계를 위한 의사 결정 지원 시스템의 개발)

  • Choi, Byoung Han
    • Journal of Korean Society of Steel Construction
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    • v.19 no.1
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    • pp.29-41
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    • 2007
  • Structural design, like other complex decision problems, involves many trade-offs among competing criteria. Although mathematical programming models are becoming increasingly realistic, they often have design limitations, that is, there are often relevant issues that cannot be easily captured. From the understanding of these limitations, a decision-support system is developed that can generate some useful alternatives as well as a single optimum value in the optimization of steel frame structures. The alternatives produced using this system are "good" with respect to modeled objectives, and yet are "different," and are often better, with respect to interesting objectives not present in the model. In this study, we created a decision-support system for designing the most cost-effective moment-resisting steel frame structures for resisting lateral loads without compromising overall stability. The proposed approach considers the cost of steel products and the cost of connections within the design process. This system makes use of an optimization formulation, which was modified to generate alternatives of optimum value, which is the result of the trade-off between the number of moment connections and total cost. This trade-off was achieved by reducing the number of moment connections and rearranging them, using the combination of analysis based on the LRFD code and optimization scheme based on genetic algorithms. To evaluate the usefulness of this system, the alternatives were examined with respect to various design aspects.