• 제목/요약/키워드: The Simulated Annealing

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DNA 연산을 이용한 기억 인출 시뮬레이션 (Memory retrieval with a DNA computing)

  • 김준식;이은석;노영균;장병탁
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2006년도 한국컴퓨터종합학술대회 논문집 Vol.33 No.1 (A)
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    • pp.34-36
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    • 2006
  • 본 연구는 특정 사물을 계속 접하면서 그 사물에 대한 기억 강도가 의식적 노력 없이도 점점 강화되는 암묵적 기억 인출과정 associative memory retrieval의 DNA 연산 가능성을 논한다. 예를 들어 한 표적 단어에 대한 노출이 이를 관찰하는 시스템에게 그 단어의 기억 강도를 강화시키는 반면, 그와 유사한 다른 단어는 천천히 감소되고 나머지 가장 다른 단어는 일찍 잊혀지는 현상을 생각할 수 있다. 이들 단어들과 알파벳 철자들을 DNA 염기서열로 표현하고 simulated annealing을 통하여 결합 결과를 얻는다. Ridge regression 형태의 supervised 학습을 통하여 한 가지 표적 단어가 많이 생성되도록 DNA 조각들의 개수 분포를 변화시켜 진행한다. 실험 예로 'tic' 'tac' 'toe' 세 가지 단어를 그 아이템으로 정하여 계속 자극받는 표적 단어의 갯수가 증가함을 DNA annealing 시뮬레이션을 통하여 확인할 수 있다. 또한 'tac' 과 't' 와 'c'를 공유하는 'tic' 의 감소 점도가 't'만을 공유하는 'toe' 보다 느림을 확인할 수 있다. 위의 실험들을 통해 연합기억associative memory의 암묵적 인출과정을 분자 층위에서 표현할 수 있음을 확인 할 수 있다.

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전산실험모형을 이용한 자동차 엔진 냉각홴의 저소음 설계 (Design of Low Noise Engine Cooling Fan for Automobile using DACE Model)

  • 심현진;박상길;조용구;오재응
    • 한국소음진동공학회논문집
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    • 제19권5호
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    • pp.509-515
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    • 2009
  • This paper proposes an optimal design scheme to reduce the noise of the engine cooling fan by adapting Kriging with two meta-heuristic techniques. An engineering model has been developed for the prediction of the noise spectrum of the engine cooling fan. The noise of the fan is expressed as the discrete frequency noise peaks at the BPF and its harmonics and line spectrum at the broad band by noise generation mechanisms. The object of this paper is to find the optimal design for noise reduction of the engine cooling fan. We firstly show a comparison of the measured and calculated noise spectra of the fan for the validation of the noise prediction program. Orthogonal array is applied as design of experiments because it is suitable for Kriging. With these simulated data, we can estimate a correlation parameter of Kriging by solving the nonlinear problem with genetic algorithm and find an optimal level for the noise reduction of the cooling fan by optimizing Kriging estimates with simulated annealing. We notice that this optimal design scheme gives noticeable results. Therefore, an optimal design for the cooling fan is proposed by reducing the noise of its system.

전산실험모형을 이용한 자동차 엔진 냉각팬의 저소음 설계 (Design of Low Noise Engine Cooling Fan for Automobile using DACE Model)

  • 심현진;이해진;이유엽;오재응
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2007년도 추계학술대회논문집
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    • pp.1307-1312
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    • 2007
  • This paper proposes an optimal design scheme to reduce the noise of the engine cooling fan by adapting Kriging with two meta-heuristic techniques. An engineering model has been developed for the prediction of the noise spectrum of the engine cooling fan. The noise of the fan is expressed as the discrete frequency noise peaks at the BPF and its harmonics and line spectrum at the broad band by noise generation mechanisms. The object of this paper is to find the Optimal Design for Noise Reduction of the Engine Cooling Fan. We firstly show a comparison of the measured and calculated noise spectra of the fan for the validation of the noise prediction program. Orthogonal array is applied as design of experiments because it is suitable for Kriging. With these simulated data, we can estimate a correlation parameter of Kriging by solving the nonlinear problem with genetic algorithm and find an optimal level for the noise reduction of the cooling fan by optimizing Kriging estimates with simulated annealing. We notice that this optimal design scheme gives noticeable results. Therefore, an optimal design for the cooling fan is proposed by reducing the noise of its system.

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크리깅을 이용한 자동차 흡기계의 소음 저감에 대한 최적 설계 (The Optimal Design for Noise Reduction of the Intake System in Automobile Using Kriging Model)

  • 심현진;류제선;차경준;오재응
    • 대한기계학회논문집A
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    • 제30권4호
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    • pp.465-472
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    • 2006
  • Recently, the regulations of the government and the concerns of people have rise to the interest in noise pollution levels as compared to other vehicles. In this area, many researchers have studied to reduce this noise in the field of automotive engineering. This paper proposes an optimal design scheme to reduce the noise of the intake system by adapting Kriging with two meta-heuristic techniques. For this, as a measuring tool for the performance of the intake system, the performance prediction software, was used. Then, the length and radius of each component of the current intake system are selected as input variables and the orthogonal arrays is adapted as a space-filling design. With these simulated data, we can estimate a correlation parameter in Kriging by solving the nonlinear problem with a genetic algorithm and find an optimal level for the intake system by optimizing Kriging estimated with simulated annealing. We notice that this optimal design scheme gives noticeable results and is a preferable way to analyze the intake system. Therefore, an optimal design for the intake system is proposed by reducing the noise of its system.

최적화 기법을 이용한 로터 축 유한요소모델 개선 (FE MODEL UPDATING OF ROTOR SHAFT USING OPTIMIZATION TECHNIQUES)

  • Kim, Yong-Han;Feng, Fu-Zhou;Yang, Bo-Suk
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2003년도 추계학술대회논문집
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    • pp.104-108
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    • 2003
  • Finite element (FE) model updating is a procedure to minimize the differences between analytical and experimental results, which can be usually posed as an optimization problem. This paper aims to introduce a hybrid optimization algorithm (GA-SA), which consists of a Genetic algorithm (GA) stage and an Adaptive Simulated Annealing (ASA) stage, to FE model updating for a shrunk shaft. A good agreement of the first four natural frequencies has been achieved obtained from GASA based updated model (FEgasa) and experiment. In order to prove the validity of GA-SA, comparisons of natural frequencies obtained from the initial FE model (FEinit), GA based updated model (FEga) and ASA based updated model (FEasa) are carried out. Simultaneously, the FRF comparisons obtained from different FE models and experiment are also shown. It is concluded that the GA, ASA, GA-SA are powerful optimization techniques which can be successfully applied to FE model updating, the natural frequencies and FRF obtained from all the updated models show much better agreement with experiment than that obtained from FEinit model. However, FEgasa is proved to be the most reasonable FE model, and also FEasa model is better than FEga model.

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디지틀 신호처리용 실리콘 컴파일러를 위한 사용자 툴 개발 (The Development of the User Interface Tool for DSP Silicon Compiler)

  • 이문기;장호랑;김종현;이승호;이광엽
    • 전자공학회논문지A
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    • 제29A권9호
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    • pp.76-84
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    • 1992
  • The DSP silicon compiler consists of language compiler, module generator, placement tool, router, layout generation tools, and simulator. In this paper, The language compiler, the module generator, placement tool, and simulator were developed and provided for the system designer. The language compiler translates the designer's system description language into the intermediate form file. The intermediate form file expresses the interconnections and specifications of the cells in the cell library. The simulator was developed and provided for the behavioral verification of the DSP system. For its implementation, the event-driven technique and the C$^{++}$ task library was used. The module generator was developed for the layout of the verified DSP system, and generates the functional block to be used in the DSP chip. And then the placement tool determines the appropriate positions of the cells in the DSP chip. In this paper, the placement tool was implemented by Min-Cut and Simulated Annealing algorithm. The placement process can be controlled by the several conditions input by the system designer.

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크리깅 근사모델을 이용한 강건설계에 관한 연구 (A Study on the Robust Design Using Kriging Surrogate Models)

  • 이권희;조용철;박경진
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2004년도 추계학술대회
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    • pp.870-875
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    • 2004
  • Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, the robust design strategy is developed based on the DACE and the global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the system. The robustness is determined by the DACE model to reduce the real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

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An online Calibration Algorithm using binary spreading code for the CDMA-based Adaptive Antenna Array

  • Lee, Chong-Hyun
    • 조명전기설비학회논문지
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    • 제20권9호
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    • pp.32-39
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    • 2006
  • In this paper, an iterative subspace-based calibration algorithm for a CDMA-based antenna array in the presence of unknown gain and phase error is presented. The algorithm does not depend on the array geometry and does not require a prior knowledge of the Directions Of Arrival (DOA) of the signals. The method requires the code sequence of a reference user only. The proposed algorithm is based on the subspace method and root finding approach, and it provides estimates of the calibration vector, the DOA and the channel impulse response, by using the code sequence of a reference user. The performance of the proposed algorithm was investigated by means of computer simulations and was verified using field data measured through a custom-built W-CDMA test-bed. The data show that experimental results match well with the theoretical calibration algorithm. Also, teh study propose an efficient algorithm using the simulated annealing technique. This algorithm overcomes the requirement of initial guessing in the subspace-based approach.

최적경로탐색문제를 위한 인공신경회로망 (An Artificial Neural Network for the Optimal Path Planning)

  • 김욱;박영문
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1991년도 하계학술대회 논문집
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    • pp.333-336
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    • 1991
  • In this paper, Hopfield & Tank model-like artificial neural network structure is proposed, which can be used for the optimal path planning problems such as the unit commitment problems or the maintenance scheduling problems which have been solved by the dynamic programming method or the branch and bound method. To construct the structure of the neural network, an energy function is defined, of which the global minimum means the optimal path of the problem. To avoid falling into one of the local minima during the optimization process, the simulated annealing method is applied via making the slope of the sigmoid transfer functions steeper gradually while the process progresses. As a result, computer(IBM 386-AT 34MHz) simulations can finish the optimal unit commitment problem with 10 power units and 24 hour periods (1 hour factor) in 5 minites. Furthermore, if the full parallel neural network hardware is contructed, the optimization time will be reduced remarkably.

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순환최소자승법을 이용한 직류도시철도 변전소의 가선전압변동 모델링 (Modelling Voltage Variation at DC Railway Traction Substation using Recursive Least Square Estimation)

  • 배창한
    • 전력전자학회논문지
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    • 제20권6호
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    • pp.534-539
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    • 2015
  • The DC overhead line voltage of an electric railway substation swings depending on the accelerating and regenerative-braking energy of trains, and it deteriorates the energy quality of the electric facility in the DC railway substation and restricts the powering and braking performance of subway trains. Recently, an energy storage system or a regenerative inverter has been introduced into railway traction substations to diminish both the variance of the overhead line voltage and the peak power consumption. In this study, the variance of the overhead line voltage in a DC railway substation is modelled by RC parallel circuits in each feeder, and the RC parameters are estimated using the recursive least mean square (RLMS) scheme. The forgetting factor values for the RLMS are selected using simulated annealing optimization, and the modelling scheme of the overhead line voltage variation is evaluated through raw data measured in a downtown railway substation.