• 제목/요약/키워드: Stochastic Evolution

검색결과 98건 처리시간 0.026초

유전자 알고리즘을 이용한 차량 승차감 개선에 관한 연구 (A Study on the Improvement of Vehicle Ride Comfort by Genetic Algorithms)

  • 백운태;성활경
    • 한국자동차공학회논문집
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    • 제6권4호
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    • pp.76-85
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    • 1998
  • Recently, Genetic Algorithm(GA) is widely adopted into a search procedure for structural optimization, which is a stochastic direct search strategy that mimics the process of genetic evolution. This methods consist of three genetics operations maned selection, crossover and mutation. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA, being zero-order method, is very simple. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher probability of converge to global optimum compared to traditional techniques which take one-point search method. In this study, a method of finding the optimum values of suspension parameters is proposed by using the GA. And vehicle is modelled as planar vehicle having 5 degree-of-freedom. The generalized coordinates are vertical motion of passenger seat, sprung mass and front and rear unsprung mass and rotate(pitch) motion of sprung mass. For rapid converge and precluding local optimum, share function which distribute chromosomes over design bound is introduced. Elitist survival model, remainder stochastic sampling without replacement method, multi-point crossover method are adopted. In the sight of the improvement of ride comfort, good result can be obtained in 5-D.O.F. vehicle model by using GA.

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A methodology to evaluate corroded RC structures using a probabilistic damage approach

  • Coelho, Karolinne O.;Leonel, Edson D.;Florez-Lopez, Julio
    • Computers and Concrete
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    • 제29권1호
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    • pp.1-14
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    • 2022
  • Several aspects influence corrosive processes in reinforced concrete (RC) structures such as environmental conditions, structural geometry and mechanical properties. Since these aspects present large randomnesses, probabilistic models allow a more accurate description of the corrosive phenomena. Besides, the definition of limit states in the reliability assessment requires a proper mechanical model. In this context, this study proposes a straightforward methodology for the mechanical-probabilistic modelling of RC structures subjected to reinforcements' corrosion. An improved damage approach is proposed to define the limit states for the probabilistic modelling, considering three main degradation phenomena: concrete cracking, rebar yielding and rebar corrosion caused either by chloride or carbonation mechanisms. The stochastic analysis is evaluated by the Monte Carlo simulation method due to the computational efficiency of the Lumped Damage Model for Corrosion (LDMC). The proposed mechanical-probabilistic methodology is implemented in a computational framework and applied to the analysis of a simply supported RC beam and a 2D RC frame. Curves illustrate the probability of failure evolution over a service life of 50 years. Moreover, the proposed model allows drawing the probability of failure map and then identifying the critical failure path for progressive collapse analysis. Collapse path changes caused by the corrosion phenomena are observed.

평균회귀확률과정을 이용한 2요인 사망률 모형 (A Two Factor Model with Mean Reverting Process for Stochastic Mortality)

  • 이강수;조재훈
    • 응용통계연구
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    • 제28권3호
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    • pp.393-406
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    • 2015
  • 본 논문은 2요인(two-factor) 사망률 모형에 평균회귀모형(mean reverting process)을 적용하여 2요인의 확률적 변동을 모형화하여 사망률리스크(mortality risk)와 장수리스크(longevity risk)를 분석하였다. 최근 고령사회로 진입한 국가들에서 사망률 개선의 둔화가 관측되고 있는 시점에서 기존의 선형증가 또는 감소의 사망률 개선 모형을 보완함에 그 목적을 두었다. 영국의 1991~2015년 사망률 자료를 이용하여 제시한 모형의 모수를 메트로폴리스 알고리듬을 이용해 추정하였고 추정된 모수 값을 이용하여 다수 시뮬레이션을 통하여 장기간의 미래 사망률 예측값을 계산하였다. 평균회귀 모형의 특성으로 인해 약 60년의 시간이 지난 뒤부터는 사망률 개선이 거의 사라져 사망률이 일정한 값에 근접하였다. 사망률 개선이 둔화되는 현상이 관측되는 특정 집단(국가, 사회)의 경우 2요인 평균회귀 모형은 장기간 사망률 예측방법의 대안으로 간주될 것으로 기대되며, 모형의 응용으로서 평균회귀율의 추정결과로부터 사망률 개선의 속도를 계량화하는 기준을 제시하였다. 끝으로, 2014년~2040 기간의 사망률 예측값을 이용하여 25년 만기 장수채권의 발행가격을 산출하였다.

확률적 구간이동 기법을 활용한 동적 포트폴리오 선정 문제에 관한 고찰 (An Investigation on Dynamic Portfolio Selection Problems Utilizing Stochastic Receding Horizon Approach)

  • 박주영;정진호;박경욱
    • 한국지능시스템학회논문지
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    • 제22권3호
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    • pp.386-393
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    • 2012
  • 최근에 금융공학 분야에 보고된 바 있는 확률적 구간이동 기반 포트폴리오 선정기법은, 최적 포트폴리오 선정을 수행하는 과정에서 부(wealth)의 변화에 대한 동적 특성 및 여러 제약조건(constraints)을 명시적으로 고려할 수 있는 방법이다. 확률적 구간이동 최적화 기반 포트폴리오 선정기법은, 그동안 구간이동 최적화 기법이 다수의 공학 문제에서 성취하였던 이론적 가치, 범용성 및 효용 등을 고려할 때 현대 포트폴리오 이론 분야에서 또 하나의 주요한 기술혁신이 될 가능성을 가지고 있다. 이에 본 논문에서는 이론적 고찰을 바탕으로 단순화된 SDP 기반 동적 포트폴리오 선정이 가능함을 관찰하고, 이를 한국 주식시장에 적용하는 시뮬레이션 연구를 수행하여 결과 수익률에 관한 의미 있는 성과를 거두었다.

지반공학 분야에 대한 차분진화 알고리즘 적용성 분석 (Analysis for Applicability of Differential Evolution Algorithm to Geotechnical Engineering Field)

  • 안준상;강경남;김산하;송기일
    • 한국지반공학회논문집
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    • 제35권4호
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    • pp.27-35
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    • 2019
  • 역해석 수행 시 상대적으로 복잡한 공간 및 목표 설계 변수가 많은 경우, 지반공학 분야에 적용하기 위한 연구를 수행하였다. 지반공학 다변수 문제에 대한 모델로 터널 분야 및 흙막이벽체에 대해서 Sharan 공식 및 Blum 방법을 사용하였다. 최적화 방법은 크게 결정론적인 방법 및 확률론적인 방법으로 구분된다. 본 연구에서는 전자 중 모의강화법(SA), 후자 중 차분진화 알고리즘(DEA), 입자 군집 최적화 알고리즘(PSO)을 선택하여 다변수 모델을 적용해서 비교하였다. 지반공학 다변수 역해석 문제에서 결정론적인 방법은 문제가 있음을 확인하였고, 차분진화 알고리즘의 우수성을 확인하였다. DEA는 Sharan의 이론 해에 대한 문제에서 평균 3.12%, Blum 문제에 대해서 평균 2.23% 오차율을 보였고, 반복 탐색 회수도 가장 작은 것으로 파악되었다. DEA 대비해서 SA는 117.39~167.13배, PSO는 2.43~6.91배의 탐색시간이 소요되었다. 지반공학 문제의 다변수 역해석에 차분진화 알고리즘을 적용하면, 계산속도 및 정확도가 향상될 것으로 기대된다.

The self induced secular evolution of gravitating systems.

  • Pichon, Christophe
    • 천문학회보
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    • 제42권2호
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    • pp.37.1-37.1
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    • 2017
  • Since the seminal work of Perrin, physicists have understood in the context of kinetic theory how ink slowly diffuses in a glass of water. The fluctuations of the stochastic forces acting on water molecules drive the diffusion of the ink in the fluid. This is the archetype of a process described by the so-called fluctuation-dissipation theorem, which universally relates the rate of diffusion to the power spectrum of the fluctuating forces. For stars in galaxies, a similar process occurs but with two significant differences, due to the long-range nature of the gravitational interaction: (i) for the diffusion to be effective, stars need to resonate, i.e. present commensurable frequencies, otherwise they only follow the orbit imposed by their mean field; (ii) the amplitudes of the induced fluctuating forces are significantly boosted by collective effects, i.e. by the fact that, because of self-gravity, each star generates a wake in its neighbours. In the expanding universe, an overdense perturbation passing a critical threshold will collapse onto itself and, through violent relaxation and mergers, rapidly converge towards a stationary, phase-mixed and highly symmetric state, with a partially frozen orbital structure. The object is then locked in a quasi-stationary state imposed by its mean gravitational field. Of particular interests are strongly responsive colder systems which, given time and kicks, find the opportunity to significantly reshuffle their orbital structure towards more likely configurations. This presentation aims to explain this long-term reshuffling called gravity-driven secular evolution on cosmic timescales, described by extended kinetic theory. I will illustrate this with radial migration, disc thickening and the stellar cluster in the galactic centre.

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Complexity Control Method of Chaos Dynamics in Recurrent Neural Networks

  • Sakai, Masao;Honma, Noriyasu;Abe, Kenichi
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.494-494
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    • 2000
  • This paper demonstrates that the largest Lyapunov exponent $\lambda$ of recurrent neural networks can be controlled by a gradient method. The method minimizes a square error $e_{\lambda}=(\lambda-\lambda^{obj})^2$ where $\lambda^{obj}$ is desired exponent. The $\lambda$ can be given as a function of the network parameters P such as connection weights and thresholds of neurons' activation. Then changes of parameters to minimize the error are given by calculating their gradients $\partial\lambda/\partialP$. In a previous paper, we derived a control method of $\lambda$via a direct calculation of $\partial\lambda/\partialP$ with a gradient collection through time. This method however is computationally expensive for large-scale recurrent networks and the control is unstable for recurrent networks with chaotic dynamics. Our new method proposed in this paper is based on a stochastic relation between the complexity $\lambda$ and parameters P of the networks configuration under a restriction. Then the new method allows us to approximate the gradient collection in a fashion without time evolution. This approximation requires only $O(N^2)$ run time while our previous method needs $O(N^{5}T)$ run time for networks with N neurons and T evolution. Simulation results show that the new method can realize a "stable" control for larege-scale networks with chaotic dynamics.

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Energy-Saving Strategy for Green Cognitive Radio Networks with an LTE-Advanced Structure

  • Jin, Shunfu;Ma, Xiaotong;Yue, Wuyi
    • Journal of Communications and Networks
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    • 제18권4호
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    • pp.610-618
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    • 2016
  • A green cognitive radio network (CRN), characterized by base stations (BSs) that conserve energy during sleep periods, is a promising candidate for realizing more efficient spectrum allocation. To improve the spectrum efficiency and achieve greener communication in wireless applications, we consider CRNs with an long term evolution advanced (LTE-A) structure and propose a novel energy-saving strategy. By establishing a type of preemptive priority queueing model with a single vacation, we capture the stochastic behavior of the proposed strategy. Using the method of matrix geometric solutions, we derive the performance measures in terms of the average latency of secondary user (SU) packets and the energy-saving degree of BSs. Furthermore, we provide numerical results to demonstrate the influence of the sleeping parameter on the system performance. Finally, we compare the Nash equilibrium behavior and social optimization behavior of the proposed strategy to present a pricing policy for SU packets.

Current Mechanistic Approaches to the Chemoprevention of Cancer

  • Steele, Vernon E.
    • BMB Reports
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    • 제36권1호
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    • pp.78-81
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    • 2003
  • The prevention of cancer is one of the most important public health and medical practices of the $21^{st}$ century. We have made much progress in this new emerging field, but so much remains to be accomplished before widespread use and practice become common place. Cancer chemoprevention encompasses the concepts of inhibition, reversal, and retardation of the cancer process. This process, called carcinogenesis, requires 20-40 years to reach the endpoint called invasive cancer. It typically follows multiple, diverse and complex pathways in a stochastic process of clonal evolution. These pathways appear amenable to inhibition, reversal or retardation at various points. We must therefore identify key pathways in the evolution of the cancer cell that can be exploited to prevent this carcinogenesis process. Basic research is identifying many genetic lesions and epigenetic processes associated with the progression of precancer to invasive disease. Many of these early precancerous lesions favor cell division over quiescence and protect cells against apoptosis when signals are present. Many oncogenes are active during early development and are reactivated in adulthood by aberrant gene promoting errors. Normal regulatory genes are mutated, making them insensitive to normal regulatory signals. Tumor suppressor genes are deleted or mutated rendering them inactive. Thus there is a wide range of defects in cellular machinery which can lead to evolution of the cancer phenotype. Mistakes may not have to appear in a certain order for cells to progress along the cancer pathway. To conquer this diverse disease, we must attack multiple key pathways at once for a predetermined period of time. Thus, agent combination prevention strategies are essential to decrease cancer morbidity. Furthermore, each cancer type may require custom combination of prevention strategies to be successful.

부분방전 신호의 비 선형적 해석 (A Nonlinear Analysis of Partial Discharge Signal)

  • 임윤석;장진강;김성홍;구자윤;김재환
    • 대한전기학회논문지:전기물성ㆍ응용부문C
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    • 제49권3호
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    • pp.169-176
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    • 2000
  • The partial discharge(PD) signal, may seems to be stochastic and merely random, was investigated using the method to discern between chaos and random signal, e.g. correlation integral, Lyapunov characteristic exponents and etc. For the purpose of obtaining experimental data, partial discharge detecting system via computer aided acoustic sensor, detect PD signal from the insulating system, was used. While this method is very different from typical statistical analysis from the point of view of a nonlinear analysis, it can provide better interpretable criterion according to the time evolution with a degradation process in the same type insulating system.

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