• Title/Summary/Keyword: SSGA

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Space Analysis of a Traditional Town for Designing Evacuation Routes considering Probability of Building Collapse

  • Hidaka, Yutaro;Mishima, Nobuo;Wakuya, Hiroshi;Hayashida, Yukuo;Okazaki, Yasuhisa;Kitagawa, Keiko;Park, Sun-gyu;Oh, Yong-sun
    • Proceedings of the Korea Contents Association Conference
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    • 2015.05a
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    • pp.7-8
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    • 2015
  • Analysis of evacuation routes for traditional buildings is important. In this study, we considered the evacuation routes using the probability of building collapse and analyzed the open space of traditional town. We considered evacuation routes from traditional houses to designated refuge places, and analysis the relationship of open space and evacuation routes.

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Design of fuzzy logic controller using genetic algorithms for the flexible manipulator (Flexible manipulator를 위한 유전 알고리즘을 이용한 퍼지 제어기 설계)

  • 허남건;이기성
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1808-1811
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    • 1997
  • A position control algorithm for a flexible manipulato is stuudied. The proposed algorithm is based on a fuzzy theroy with a Steady State Genetic Algorithm(SSGA). The conventional fuzzy methods need expert's knowledges or human experiences. The SSGA, which is one of the optimization algorithms, tunes automatically the input-output membership parameters and fuzzy rules. The computer simulation is presented ot illustrate the approaches. Finally we applied a fuzzy theory with a SSGA to aposition control of a flexible manipulator.

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A temporary evacuation area like open space analysis for disaster prevention town considering probability of street blockade-

  • Hidaka, Yutaro;Mishima, Nobuo;Wakuya, Hiroshi;Hayashida, Yukuo;Okazaki, Yasuhisa;Kitagawa, Keiko;Park, Sun-gyu;Oh, Yong-sun
    • Proceedings of the Korea Contents Association Conference
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    • 2016.05a
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    • pp.239-240
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    • 2016
  • Traditional town with wooden houses like Japanese historic local town is vulnerable to disaster. Wooden houses crowed in this study area, there is no gap between buildings and buildings. When disaster occurs, they can not use evacuation routes based on the value of probability of rubble flow. Disaster prevention design of traditional town using spatial information for residents is a modern idea in the field of disaster prevention study. Therefore, it is basically important and effective to create information, especially on the current situation such as dangerousness of the area. Here, we report on a disaster prevention design regarding probability of street blockade and probability of rubble flow at a large earthquake directly under our study area. In this study, we explain about necessity of temporary evacuation areas like open space. As a result, we found some ideas to secure evacuation routes from traditional houses to designated refuge places using temporary evacuation areas.

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Controller Design Using a Fuzzy Theory and Genetic Algorithm (퍼지이론과 유전알고리즘의 합성에 의한 제어기설계)

  • Oh, Jong-In;Lee, Kee-Seong
    • Proceedings of the KIEE Conference
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    • 1998.11b
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    • pp.645-647
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    • 1998
  • A position control algorithm for a inverted pendulum is studied. The proposed algorithm is based on a fuzzy theory and a steady state genetic algorithm(SSGA). The conventional fuzzy methods need expert's knowledges or human experiences. The SSGA, which is a optimization algorithm, tunes the input-output membership parameters and fuzzy rules automatically. The computer simulation to control a inverted pendulum is presented to illustrate the approaches.

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Design of a Controller for a Flexible Manipulator Using Fuzzy Theory and Genetic Algorithm (피지이론과 유전알고리츰의 합성에 의한 Flexible Manipulator 제어기 설계)

  • Lee, Kee-Seong;Cho, Hyun-Chul
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.1
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    • pp.61-66
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    • 2002
  • A position control algorithm for a flexible manipulator is studied. The proposed algorithm is based on a fuzzy theory with a Steady State Genetic Algorithm(SSGA) and an Adaptive Genetic Algorithms(AGA). The proposed controller for a flexible manipulator have decreased 90.8%, 31.8%, 31.3% in error when compared with a conventional fuzzy controller, fuzzy controller using neural network, fuzzy controller using evolution strategies, respectively when the weight and the velocity of end-point are 0.8k9 and 1m/s, respectively.

The Study on the Optimum Design of Acoustic Interference Model by Genetic Algorithm (유전자 알고리즘을 이용한 음향 간섭 모델 최적화 설계)

  • Lee, Jae-Hwan;Jang, Kang-Seok
    • Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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    • 2003.10a
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    • pp.18-23
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    • 2003
  • The Objective of this research is to find the optimal design of the Noise Reduction Interference Model (NRIM) which is recently invented. Without optimization, the NRIM has been successful to reduce the urban noise induced by trains and automobiles. While it is used with the barrier on the road, there is a strong desire to reduce noise more. Yet the only remedy is to make the barrier higher with cost increase. Therefore, the optimal design is necessary to reduce noise while maintaining the barrier height. More efficient Genetic Algorithm is used to find the optimal shape of NRIM with the reduction of noise lever up to 15 dB. also BEM is used to verify the optimal design results.

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The Study on the Optimum Design of Acoustic Interference Model for Traffic Noise Reduction (교통소음저감을 위한 음향간섭모델의 최적화설계에 관한 연구)

  • 장강석;김영찬;김두훈;이재환
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2004.05a
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    • pp.724-729
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    • 2004
  • An experimental method to investigate the dynamic characteristics of buoys in extreme environmental condition is established. Because the buoy model requires a resonable size for accurate experiment, the test condition in model basin that satisfies the similarity law is hardly compatible with capability of test facilities. It is suggested that the linear wave component that is unable to satisfy similarity is separated with others‥‥‥

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Detection and quantification of structural damage under ambient vibration environment

  • Yun, Gun Jin
    • Structural Engineering and Mechanics
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    • v.42 no.3
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    • pp.425-448
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    • 2012
  • In this paper, a new damage detection and quantification method has been presented to perform detection and quantification of structural damage under ambient vibration loadings. To extract modal properties of the structural system under ambient excitation, natural excitation technique (NExT) and eigensystem realization algorithm (ERA) are employed. Sensitivity matrices of the dynamic residual force vector have been derived and used in the parameter subset selection method to identify multiple damaged locations. In the sequel, the steady state genetic algorithm (SSGA) is used to determine quantified levels of the identified damage by minimizing errors in the modal flexibility matrix. In this study, performance of the proposed damage detection and quantification methodology is evaluated using a finite element model of a truss structure with considerations of possible experimental errors and noises. A series of numerical examples with five different damage scenarios including a challengingly small damage level demonstrates that the proposed methodology can efficaciously detect and quantify damage under noisy ambient vibrations.

A Study on Acoustic Radiation Reduction of a Vibrating Panel by Using Particle Swarm Optimization Algorithm (군집행동 알고리즘을 이용한 판넬구조물의 방사소음저감에 관한 연구)

  • Jeon, Jin-Young
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.19 no.5
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    • pp.482-490
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    • 2009
  • In this paper, the author proposes a new method for acoustic radiation optimum design to minimize noise from a vibrating panel-like structure using a collaborative population-based search method called the particle swarm optimization algorithm(PSOA). The PSOA is a parallel evolutionary computation technique initially developed by Kennedy and Eberhart. The acoustic radiation optimization method based on the PSOA consists of two processes. In the first process, the acoustic radiation analysis by an integrated p-version FEM/BEM, which was developed by using MATLAB, is performed to evaluate the exterior acoustic radiation field of the panel. The second process is to search the optimum design variables: 1) Shape of Bezier curves and 2) Shape and position of ribs, to minimize noise from the panel using the PSOA. The optimization method based on the PSOA is compared to that based on the steady state genetic algorithm(SSGA) in order to verify the effectiveness and validity of the optimal solution by PSOA. Finally, it is shown that the optimal designs of the panel obtained by using the PSOA can achieve effective reductions in radiated sound power.

A two-stage damage detection approach based on subset selection and genetic algorithms

  • Yun, Gun Jin;Ogorzalek, Kenneth A.;Dyke, Shirley J.;Song, Wei
    • Smart Structures and Systems
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    • v.5 no.1
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    • pp.1-21
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    • 2009
  • A two-stage damage detection method is proposed and demonstrated for structural health monitoring. In the first stage, the subset selection method is applied for the identification of the multiple damage locations. In the second stage, the damage severities of the identified damaged elements are determined applying SSGA to solve the optimization problem. In this method, the sensitivities of residual force vectors with respect to damage parameters are employed for the subset selection process. This approach is particularly efficient in detecting multiple damage locations. The SEREP is applied as needed to expand the identified mode shapes while using a limited number of sensors. Uncertainties in the stiffness of the elements are also considered as a source of modeling errors to investigate their effects on the performance of the proposed method in detecting damage in real-life structures. Through a series of illustrative examples, the proposed two-stage damage detection method is demonstrated to be a reliable tool for identifying and quantifying multiple damage locations within diverse structural systems.