• 제목/요약/키워드: non-Markov evolution

검색결과 6건 처리시간 0.021초

A NON-MARKOVIAN EVOLUTION MODEL OF HIV POPULATION WITH BUNCHING BEHAVIOUR

  • Sridharan, V.;Jayshree, P.R.
    • Journal of applied mathematics & informatics
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    • 제5권3호
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    • pp.785-796
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    • 1998
  • In this paper we propose a model of HIv population through method of phases with non-Markovian evolution of immi-gration. The analysis leads to an explicit differnetial equations for the generating functions of the total population size. The detection process of antibodies (against the antigen of virus) is analysed and an explicit expression for the correlation functions are provided. A measure of bunching is also introduced for some particular choice of parameters.

Bayesian Analysis of Binary Non-homogeneous Markov Chain with Two Different Time Dependent Structures

  • Sung, Min-Je
    • Management Science and Financial Engineering
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    • 제12권2호
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    • pp.19-35
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    • 2006
  • We use the hierarchical Bayesian approach to describe the transition probabilities of a binary nonhomogeneous Markov chain. The Markov chain is used for describing the transition behavior of emotionally disturbed children in a treatment program. The effects of covariates on transition probabilities are assessed using a logit link function. To describe the time evolution of transition probabilities, we consider two modeling strategies. The first strategy is based on the concept of exchangeabiligy, whereas the second one is based on a first order Markov property. The deviance information criterion (DIC) measure is used to compare models with two different time dependent structures. The inferences are made using the Markov chain Monte Carlo technique. The developed methodology is applied to some real data.

Non-Stationary 추이확률 모형에 의한 농작물의 체계에 관한 연구 (A study on the planted system of agricultural crops using non-stationary transition probability model)

  • 강정혁;김여근
    • 경영과학
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    • 제8권1호
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    • pp.3-11
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    • 1991
  • Non-Stationary transition probabilities models which is incorporated into a Markov framework with exogenous variables to account for some of variability are discussed, and extended for alternative procedure. Also as an application of the methodology, the size change of aggregate time-series data on the planted system of agricultural crops is estimated, and evaluated for the precision of time-varying evolution statistically.

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Performance-based remaining life assessment of reinforced concrete bridge girders

  • Anoop, M.B.;Rao, K. Balaji;Raghuprasad, B.K.
    • Computers and Concrete
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    • 제18권1호
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    • pp.69-97
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    • 2016
  • Performance-based remaining life assessment of reinforced concrete bridge girders, subject to chloride-induced corrosion of reinforcement, is addressed in this paper. Towards this, a methodology that takes into consideration the human judgmental aspects in expert decision making regarding condition state assessment is proposed. The condition of the bridge girder is specified by the assignment of a condition state from a set of predefined condition states, considering both serviceability- and ultimate- limit states, and, the performance of the bridge girder is described using performability measure. A non-homogeneous Markov chain is used for modelling the stochastic evolution of condition state of the bridge girder with time. The thinking process of the expert in condition state assessment is modelled within a probabilistic framework using Brunswikian theory and probabilistic mental models. The remaining life is determined as the time over which the performance of the girder is above the required performance level. The usefulness of the methodology is illustrated through the remaining life assessment of a reinforced concrete T-beam bridge girder.

Opportunistic Spectrum Access Based on a Constrained Multi-Armed Bandit Formulation

  • Ai, Jing;Abouzeid, Alhussein A.
    • Journal of Communications and Networks
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    • 제11권2호
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    • pp.134-147
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    • 2009
  • Tracking and exploiting instantaneous spectrum opportunities are fundamental challenges in opportunistic spectrum access (OSA) in presence of the bursty traffic of primary users and the limited spectrum sensing capability of secondary users. In order to take advantage of the history of spectrum sensing and access decisions, a sequential decision framework is widely used to design optimal policies. However, many existing schemes, based on a partially observed Markov decision process (POMDP) framework, reveal that optimal policies are non-stationary in nature which renders them difficult to calculate and implement. Therefore, this work pursues stationary OSA policies, which are thereby efficient yet low-complexity, while still incorporating many practical factors, such as spectrum sensing errors and a priori unknown statistical spectrum knowledge. First, with an approximation on channel evolution, OSA is formulated in a multi-armed bandit (MAB) framework. As a result, the optimal policy is specified by the wellknown Gittins index rule, where the channel with the largest Gittins index is always selected. Then, closed-form formulas are derived for the Gittins indices with tunable approximation, and the design of a reinforcement learning algorithm is presented for calculating the Gittins indices, depending on whether the Markovian channel parameters are available a priori or not. Finally, the superiority of the scheme is presented via extensive experiments compared to other existing schemes in terms of the quality of policies and optimality.

비정상성 가뭄빈도 해석 기법에 따른 가뭄 심도-지속기간-재현기간 곡선 유도에 관한 연구 (A Study on derivation of drought severity-duration-frequency curve through a non-stationary frequency analysis)

  • 정민수;박서연;장호원;이주헌
    • 한국수자원학회논문집
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    • 제53권2호
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    • pp.107-119
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    • 2020
  • 본 연구는 한반도의 관측 강우자료를 기반으로 하여 과거의 가뭄 특성을 파악함과 동시에 RCP 8.5 기후변화 시나리오를 활용한 장래 발생 가능한 극치 가뭄에 대한 장기전망을 수행하였다. 정량적인 가뭄 분석을 위해 기상학적 가뭄지수인 표준강수지수(Standardized Precipitation Index, SPI)를 적용하였으며 일단위 강우 관측 자료 및 RCP 시나리오를 단일한 장기 시계열 자료로 구축하여 1, 3, 6, 9, 12개월 지속기간의 SPI 입력인자로 활용하였다. 한반도의 지역별 가뭄특성 분석을 위한 대상 강우관측소는 1954년 시점부터 강우 자료를 보유하고 있는 12개 관측 지점을 선정하였으며, 동일 지점의 10개 GCM(General Circulation Model)을 적용하였다. 기후변화에 따른 가뭄 특성 변화 분석을 위해 강우발생일수와 총강수량에 대한 12개 강우관측소별 추세 변동 분석 및 군집화를 수행하였다. 샘플링 기법을 활용한 비정상성 빈도분석을 위해 베이지안 기반의 DE(Differential Evolution)와 MCMC(Markov Chain Monte Carlo)를 결합한 DEMC 기법을 채택하였고, 비정상성 가뭄빈도해석을 통하여 12개 지점별 SDF(Severity-Duration-Frequency) 곡선을 유도하였다. 비정상성을 가정한 장기 수문자료를 보유한 지점들의 SDF 곡선 산정을 통해 미래의 가뭄에 대한 정량적인 전망을 수행하였다. 장기시계열 자료를 보유한 12개 지점의 군집분석을 수행한 결과 Zone 1-2, 2, 3-2에 해당하는 제주를 제외한 전주, 광주, 여순, 목포, 추풍령 등에서 장래에 가뭄발생 위험이 높은 것으로 분석되었다. 장래 발생 가능한 가뭄 위험성을 정량적으로 파악함으로써 미래 가뭄관리 정책에 충분히 활용될 수 있을 것으로 기대된다.