• 한국지능시스템학회논문지
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• 제16권4호
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• pp.396-401
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• 2006

순환결합형 신경회로망은 복수 개의 리미트사이클을 생성하며 따라서, 많은 동적 정보를 저장할 수 있는 메모리 시스템으로 사용할 수 있다는 것이 알려져 있다. 본 논문에서는 각 뉴런이 최근접 뉴런에만 이진화한 결합하중 ${\pm}1$로 연결된 연속 시간모델 순환결합형 신경회로망을 구현하였다. 그리고 이런 회로망을 통해 생성되는 리미트사이클의 수와 패턴을 시뮬레이션을 통하여 나타내었다. 또한 카오스 신호를 인가하여 리미트사이클 사이의 천이 가능성을 입증하였다. 특히, 카오스 신호 이외의 랜덤 노이즈를 이용한 해석을 통하여 동적 신경회로망에 카오스 노이즈를 인가하는 경우의 유효성을 검토하였다.

• Smart Structures and Systems
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• 제31권2호
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• pp.113-130
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• 2023

Hybrid simulation (HS) has attracted community attention in recent years as an efficient and effective experimental technique for structural performance evaluation in size-limited laboratories. Traditional hybrid simulations usually take deterministic properties for their numerical substructures therefore could not account for inherent uncertainties within the engineering structures to provide probabilistic performance assessment. Reliable structural performance evaluation, therefore, calls for stochastic hybrid simulation (SHS) to explicitly account for substructure uncertainties. The experimental design of SHS is explored in this study to account for uncertainties within analytical substructures. Both computational simulation and laboratory experiments are conducted to evaluate the pseudo-random Sobol sequence for the experimental design of SHS. Meta-modeling through polynomial chaos expansion (PCE) is established from a computational simulation of a nonlinear single-degree-of-freedom (SDOF) structure to evaluate the influence of nonlinear behavior and ground motions uncertainties. A series of hybrid simulations are further conducted in the laboratory to validate the findings from computational analysis. It is shown that the Sobol sequence provides a good starting point for the experimental design of stochastic hybrid simulation. However, nonlinear structural behavior involving stiffness and strength degradation could significantly increase the number of hybrid simulations to acquire accurate statistical estimation for the structural response of interests. Compared with the statistical moments calculated directly from hybrid simulations in the laboratory, the meta-model through PCE gives more accurate estimation, therefore, providing a more effective way for uncertainty quantification.

• 지식경영연구
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• 제22권4호
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• pp.119-133
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• 2021

각 산업에서 대량의 데이터가 생산되면서, 빠른 경영 의사결정을 위해 시계열 패턴 예측 연구가 수많이 진행되고 있다. 하지만 데이터에 내재된 불확실성으로 인해 비선형 시계열 데이터의 특정 패턴을 예측하는 데 한계가 존재하고, 기업경영의 전략적 의사결정 어려움이 존재한다. 또한, 최근 수십 년간 불규칙한 랜덤워크 모형의 시계열 데이터 예측을 위해 산업의 목적에 맞는 금융시장 데이터를 대상으로 다양한 연구가 진행되고 있지만, 특정 규칙을 예측하고 지속가능의 기업목적 달성 어려움이 있다. 본 연구에서는 룰렛 데이터와 금융시장 데이터를 Chaos 분석기법을 이용하여 예측 결과를 비교분석하고 유의미한 결과를 도출하였다. 그리고, 본 연구는 카오스 분석이 시계열 자료를 분석하는데 있어 새로운 방법을 모색하는데 유용함을 확인하였다. 룰렛 게임의 특성을 한국 주가지수 선물의 시계열과 비교 분석하여 추세가 확인되는 경우 예측력을 높일 수 있다는 점을 도출하였으며, 불확실성이 높고 랜덤워크가 존재하는 비선형 시계열 데이터가 특정한 패턴을 가지고 있는지 판단하는데 의의가 있다.

• Structural Engineering and Mechanics
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• 제45권5호
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• pp.595-611
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• 2013

This paper aims to compare three collocation point methods associated with the odd order stochastic response surface method (SRSM) in a systematical and quantitative way. The SRSM with the Hermite polynomial chaos is briefly introduced first. Then, three collocation point methods, namely the point method, the root method and the without origin method underlying the odd order SRSMs are highlighted. Three examples are presented to demonstrate the accuracy and efficiency of the three methods. The results indicate that the condition that the Hermite polynomial information matrix evaluated at the collocation points has a full rank should be satisfied to yield reliability results with a sufficient accuracy. The point method and the without origin method are much more efficient than the root method, especially for the reliability problems involving a large number of random variables or requiring complex finite element analysis. The without origin method can also produce sufficiently accurate reliability results in comparison with the point and root methods. Therefore, the origin often used as a collocation point is not absolutely necessary. The odd order SRSMs with the point method and the without origin method are recommended for the reliability analysis due to their computational accuracy and efficiency. The order of SRSM has a significant influence on the results associated with the three collocation point methods. For normal random variables, the SRSM with an order equaling or exceeding the order of a performance function can produce reliability results with a sufficient accuracy. The order of SRSM should significantly exceed the order of the performance function involving strongly non-normal random variables.

• Wind and Structures
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• 제34권1호
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• pp.127-136
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• 2022

In this work a multi-fidelity non-intrusive polynomial chaos (MF-NIPC) has been applied to a structural wind engineering problem in architectural design for the first time. In architectural design it is important to design structures that are safe in a range of wind directions and speeds. For this reason, the computational models used to design buildings and bridges must account for the uncertainties associated with the interaction between the structure and wind. In order to use the numerical simulations for the design, the numerical models must be validated by experi-mental data, and uncertainties contained in the experiments should also be taken into account. Uncertainty Quantifi-cation has been increasingly used for CFD simulations to consider such uncertainties. Typically, CFD simulations are computationally expensive, motivating the increased interest in multi-fidelity methods due to their ability to lev-erage limited data sets of high-fidelity data with evaluations of more computationally inexpensive models. Previous-ly, the multi-fidelity framework has been applied to CFD simulations for the purposes of optimization, rather than for the statistical assessment of candidate design. In this paper MF-NIPC method is applied to flow around a rectan-gular 5:1 cylinder, which has been thoroughly investigated for architectural design. The purpose of UQ is validation of numerical simulation results with experimental data, therefore the radius of curvature of the rectangular cylinder corners and the angle of attack are considered to be random variables, which are known to contain uncertainties when wind tunnel tests are carried out. Computational Fluid Dynamics (CFD) simulations are solved by a solver that employs the Finite Element Method (FEM) for two turbulence modeling approaches of the incompressible Navier-Stokes equations: Unsteady Reynolds Averaged Navier Stokes (URANS) and the Large Eddy simulation (LES). The results of the uncertainty analysis with CFD are compared to experimental data in terms of time-averaged pressure coefficients and bulk parameters. In addition, the accuracy and efficiency of the multi-fidelity framework is demonstrated through a comparison with the results of the high-fidelity model.

• 한국전자통신학회논문지
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• 제9권10호
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• pp.1145-1152
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• 2014

RFID(Radio-Frequency IDentification)시스템은 무선으로 사물을 식별하는 기술로 물류, 운송, 유통, 재고관리 등과 같은 물품관리를 획기적으로 개선할 수 있는 새로운 방법이다. 그러나 무선을 사용하고 있는 RFID는 통신구간에 대한 보안의 취약성 때문에 정보 누출 및 변조 같은 위험성을 가지고 있다. 우리는 이런 RFID 통신 시스템에 복잡계의 대표적인 계인 Tent-Map을 적용하여 새로운 인증 프로토콜을 설계하였다. 복잡계의 대표적인 특징인 초기치 민감성과 불규칙성을 RFID의 Reader 와 Tag에 적용하여 보다 견고하고 간략한 인증시스템을 설계하였다. 본 논문에서 보인 복잡계를 이용한 RFID 인증 프로토콜 설계는 기존의 Hash 함수나 난수에 의존되었던 인증 시스템에 차별화된 새로운 방법으로 그 활용성을 검증하는데 그 목적이 있다.