• 제목/요약/키워드: Deterministic method

검색결과 777건 처리시간 0.027초

시간 제한 조건을 가진 자유 선택 신호 전이 그래프로부터 비동기 회로의 합성 (Synthesis of Asynchronous Circuits from Free-Choice Signal Transition Graphs with Timing Constraints)

  • 정성태;정석태
    • 정보처리학회논문지A
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    • 제9A권1호
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    • pp.61-74
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    • 2002
  • 본 논문에서는 시간 제한 조건을 가진 자유 선택 신호 전이 그래프로부터 비동기 회로를 합성하는 방법을 기술한다. 이 방법에서는 상태 그래프를 생성하지 않고 신호 전이 그래프로부터 직접 신호 전이들간의 관계를 구하여 비동기 회로를 합성한다. 본 논문의 합성 방법에서는 자유 선택 신호 전이 그래프를 선택 행위가 없는 결정성 신호 전이 그래프에 대하여 타이밍 분석을 수행하여 임의의 두 신호 전이 사이의 시간 제약 병렬 관계와 시간 제약 인과 관계를 구한다. 다음에는 이 관계들을 이용하여 각 결정성 신호 전이 그래프에 대한 합성을 수행하고 그 결과를 합병함으로써 전체 회로를 합성한다. 실험 결과에 의하면 본 논문에서 제안한 합성 방법은 상태 공간이 큰 회로에 대하여 현저하게 합성시간을 단축시킬 수 있을 뿐 만 아니라 기존의 상태 그래프 기반 합성 방법과 비교하여 거의 같은 면적의 회로를 합성한다.

Multi-Objective Stochastic Optimization in Water Resources System

  • Shim, Soon Bo
    • 한국경영과학회지
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    • 제8권1호
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    • pp.41-59
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    • 1983
  • The purpose of this paper is to present a method of multi-objective, stochastic optimization in water resources system which investigates the development of potential non-normal deterministic equivalents for subsequent use in multiobjective stochastic programming methods, Given probability statement involving a function of several random variables, it is often possible to obtain a deterministic equivalent of it that does not include any orginal random variables. A Stochastic trade-off technique-MSTOT is suggested to help a decision maker achieve satisfactory levels for several objective functions. This makes use of deterministic equivalents to handle random variables in the objective functions. The emphasis is in the development of non-normal deterministic equivalents for use in multiobjective stochastic techniques.

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Deep Deterministic Policy Gradient 알고리즘을 응용한 자전거의 자율 주행 제어 (Autonomous control of bicycle using Deep Deterministic Policy Gradient Algorithm)

  • 최승윤;레 팜 투옌;정태충
    • 융합보안논문지
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    • 제18권3호
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    • pp.3-9
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    • 2018
  • DDPG(Deep Deterministic Policy Gradient)알고리즘은 인공신경망과 강화학습을 사용하여 학습하는 알고리즘이다. 최근 많은 연구가 이루어지고 있는 강화학습과 관련된 연구 중에서도 DDPG 알고리즘은 오프폴리시로 학습하기 때문에 잘못된 행동이 누적되어 학습에 영향을 미치는 경우를 방지하는 장점이 있다. 본 연구에서는 DDPG 알고리즘을 응용하여 자전거를 자율주행 하도록 제어하는 실험을 진행하였다. 다양한 환경을 설정하여 시뮬레이션을 진행하였고 실험을 통해서 사용된 방법이 시뮬레이션 상에서 안정적으로 동작함을 보였다.

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Probabilistic bearing capacity of strip footing on reinforced anisotropic soil slope

  • Halder, Koushik;Chakraborty, Debarghya
    • Geomechanics and Engineering
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    • 제23권1호
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    • pp.15-30
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    • 2020
  • The probabilistic bearing capacity of a strip footing placed on the edge of a purely cohesive reinforced soil slope is computed by combining lower bound finite element limit analysis technique with random field method and Monte Carlo simulation technique. To simulate actual field condition, anisotropic random field model of undrained soil shear strength is generated by using the Cholesky-Decomposition method. With the inclusion of a single layer of reinforcement, dimensionless bearing capacity factor, N always increases in both deterministic and probabilistic analysis. As the coefficient of variation of the undrained soil shear strength increases, the mean N value in both unreinforced and reinforced slopes reduces for particular values of correlation length in horizontal and vertical directions. For smaller correlation lengths, the mean N value of unreinforced and reinforced slopes is always lower than the deterministic solutions. However, with the increment in the correlation lengths, this difference reduces and at a higher correlation length, both the deterministic and probabilistic mean values become almost equal. Providing reinforcement under footing subjected to eccentric load is found to be an efficient solution. However, both the deterministic and probabilistic bearing capacity for unreinforced and reinforced slopes reduces with the consideration of loading eccentricity.

Probabilistic multi-objective optimization of a corrugated-core sandwich structure

  • Khalkhali, Abolfazl;Sarmadi, Morteza;Khakshournia, Sharif;Jafari, Nariman
    • Geomechanics and Engineering
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    • 제10권6호
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    • pp.709-726
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    • 2016
  • Corrugated-core sandwich panels are prevalent for many applications in industries. The researches performed with the aim of optimization of such structures in the literature have considered a deterministic approach. However, it is believed that deterministic optimum points may lead to high-risk designs instead of optimum ones. In this paper, an effort has been made to provide a reliable and robust design of corrugated-core sandwich structures through stochastic and probabilistic multi-objective optimization approach. The optimization is performed using a coupling between genetic algorithm (GA), Monte Carlo simulation (MCS) and finite element method (FEM). To this aim, Prob. Design module in ANSYS is employed and using a coupling between optimization codes in MATLAB and ANSYS, a connection has been made between numerical results and optimization process. Results in both cases of deterministic and probabilistic multi-objective optimizations are illustrated and compared together to gain a better understanding of the best sandwich panel design by taking into account reliability and robustness. Comparison of results with a similar deterministic optimization study demonstrated better reliability and robustness of optimum point of this study.

Transient Simulation of Graphene Sheets using a Deterministic Boltzmann Equation Solver

  • Hong, Sung-Min
    • JSTS:Journal of Semiconductor Technology and Science
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    • 제17권2호
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    • pp.288-293
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    • 2017
  • Transient simulation capability with an implicit time derivation method is a missing feature in deterministic Boltzmann equation solvers. The H-transformation, which is critical for the stable simulation of nanoscale devices, introduces difficulties for the transient simulation. In this work, the transient simulation of graphene sheets is reported. It is shown that simulation of homogeneous systems can be done without abandoning the H-transformation, as much as a specially designed discretization method is employed. The AC mobility and step response of the graphene sheet on the $SiO_2$ substrate are simulated.

Deterministic Bipolar Compressed Sensing Matrices from Binary Sequence Family

  • Lu, Cunbo;Chen, Wengu;Xu, Haibo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권6호
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    • pp.2497-2517
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    • 2020
  • For compressed sensing (CS) applications, it is significant to construct deterministic measurement matrices with good practical features, including good sensing performance, low memory cost, low computational complexity and easy hardware implementation. In this paper, a deterministic construction method of bipolar measurement matrices is presented based on binary sequence family (BSF). This method is of interest to be applied for sparse signal restore and image block CS. Coherence is an important tool to describe and compare the performance of various sensing matrices. Lower coherence implies higher reconstruction accuracy. The coherence of proposed measurement matrices is analyzed and derived to be smaller than the corresponding Gaussian and Bernoulli random matrices. Simulation experiments show that the proposed matrices outperform the corresponding Gaussian, Bernoulli, binary and chaotic bipolar matrices in reconstruction accuracy. Meanwhile, the proposed matrices can reduce the reconstruction time compared with their Gaussian counterpart. Moreover, the proposed matrices are very efficient for sensing performance, memory, complexity and hardware realization, which is beneficial to practical CS.

DEVELOPMENT OF THE HANSEL-SPITTEL CONSTITUTIVE MODEL GAZED FROM A PROBABILISTIC PERSPECTIVE

  • LEE, KYUNGHOON;KIM, JI HOON;KANG, BEOM-SOO
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제21권3호
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    • pp.155-165
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    • 2017
  • The Hansel-Spittel constitutive model requires a total of nine parameters for flow stress prediction. Typically, the parameters are estimated by least squares methods for given tensile test measurements from a deterministic perspective. In this research we took a different approach, a probabilistic viewpoint, to see through the development of the Hansel-Spittel constitutive model. This perspective change showed that deterministic least squares methods are closely related to statistical maximum likelihood methods via Gaussian noise assumption. More intriguingly, this perspective shift revealed that the Hansel-Spittel constitutive model may leave out deterministic trends in residuals despite nearly perfect agreement with measurements. With tensile test measurements of AA1070 aluminum alloy, we demonstrated this deficiency of the Hansel-Spittel constitutive model, suggesting room for improvement.

Deterministic and reliability-based design of necessary support pressures for tunnel faces

  • Li, Bin;Yao, Kai;Li, Hong
    • Geomechanics and Engineering
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    • 제22권1호
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    • pp.35-48
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    • 2020
  • This paper provides methods for the deterministic and reliability-based design of the support pressures necessary to prevent tunnel face collapse. The deterministic method is developed by extending the use of the unique load multiplier, which is embedded within OptumG2/G3 with the intention of determining the maximum load that can be supported by a system. Both two-dimensional and three-dimensional examples are presented to illustrate the applications. The obtained solutions are validated according to those derived from the existing methods. The reliability-based method is developed by incorporating the Response Surface Method and the advanced first-order second-moment reliability method into the bisection algorithm, which continuously updates the support pressure within previously determined brackets until the difference between the computed reliability index and the user-defined value is less than a specified tolerance. Two-dimensional reliability-based support pressure is compared and validated via Monte Carlo simulations, whereas the three-dimensional solution is compared with the relationship between the support pressure and the resulting reliability index provided in the existing literature. Finally, a parametric study is carried out to investigate the influences of factors on the required support pressure.

토사면의 한계상태 설계법에 관한 연구 (A Study of Limit State Design Method in Soil Slope)

  • 정기훈;김종민;장범수
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2005년도 춘계 학술발표회 논문집
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    • pp.129-136
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    • 2005
  • The deterministic analysis method has generally used to evaluate the slope stability and it evaluates the slope stability with decision value that is a representative value of design variables. However, one of disadvantages in the deterministic approach is there is not able to consider the uncertainty of soil strength properties, even though it is the biggest influential parameter of the slope stability. On the other hand, the limit state design(LSD) can take a consideration of uncertainties and computes both the reliability index and the probability of failure. LSD method is capable of overcoming the disadvantages of deterministic method and evaluating the slope stability more reliably. In this study, both the mean value and standard deviation of the internal land's representative soil strength properties applied to process the LSD method. The major purpose of this study is to gauge the general applicability of the limit state design in soil slope and to weigh the comparative validity of the proposed partial safety factor. In order to reach the aim of this study, the partial safety factor and resistance factor which totally satisfied the slope's overall safety factor were calculated by the load and resistance safety factor design (LRFD).

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