• Title/Summary/Keyword: 오류역전파신경망

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Optimization of Transonic Airfoil Using GA Based on Neural Network and Multiple Regression Model (유전 알고리듬과 반응표면을 이용한 천음속 익형의 최적설계)

  • Kim, Yun-Sik;Kim, Jong-Hun;Lee, Jong-Soo
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.12
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    • pp.2556-2564
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    • 2002
  • The design of airfoil had practiced by repeat tests in its first stage, though an airfoil has as been designed based on simulations according to techniques of computational fluid dynamics. Here, using of traditional optimization is unsuitable because a state of flux is hypersensitive to the shape of airfoil. Therefore the paper optimized the shape of airfoil in transonic region using a genetic algorithm (GA). Response surfaces are based on back propagation neural network (BPN) and regression model. Training data of BPN and regression model were obtained by computational fluid dynamic analysis using CFD-ACE, and each analysis has been designed by design of experiments.

Optimization of T-Structure Supporting Steering System Using μGA (승용차용 스티어링시스템 지지 T-형구조물의 최적설계)

  • Lee Jong Soo;Kim Sung Chul
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.6 s.237
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    • pp.809-814
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    • 2005
  • The goal of this paper is to minimize the weight of the T-structure supporting steering system in reducing the vibration level on steering wheel which could be amplified by the resonance. Presently, requirements for reducing noise, vibration and harshness (NVH) in automotive area are more stringent than ever. One of them is the vibration of steering system which occurs sometimes at high speeds or when the engine is idling. Besides, the reduction of weight is also one of requirements for improvement of vehicle performance. This paper used the micro genetic algorithm as an optimization method to satisfy above two requirements. The whole T-structure assembly including steering column was used for frequency analysis.