• Title/Summary/Keyword: continuous-space discrete-state Markov process

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A Markov-based prediction model of tunnel geology, construction time, and construction costs

  • Mahmoodzadeh, Arsalan;Mohammadi, Mokhtar;Ali, Hunar Farid Hama;Salim, Sirwan Ghafoor;Abdulhamid, Sazan Nariman;Ibrahim, Hawkar Hashim;Rashidi, Shima
    • Geomechanics and Engineering
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    • v.28 no.4
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    • pp.421-435
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    • 2022
  • The necessity of estimating the time and cost required for tunnel construction has led to extensive research in this regard. Since geological conditions are significant factors in terms of time and cost of road tunnels, considering these conditions is crucial. Uncertainties about the geological conditions of a tunnel alignment cause difficulties in planning ahead of the required construction time and costs. In this paper, the continuous-space, discrete-state Markov process has been used to predict geological conditions. The Monte-Carlo (MC) simulation (MCS) method is employed to estimate the construction time and costs of a road tunnel project using the input data obtained from six tunneling expert questionnaires. In the first case, the input data obtained from each expert are individually considered and in the second case, they are simultaneously considered. Finally, a comparison of these two modes based on the technique presented in this article suggests considering views of several experts simultaneously to reduce uncertainties and ensure the results obtained for geological conditions and the construction time and costs.

Parallel Gaussian Processes for Gait and Phase Analysis (보행 방향 및 상태 분석을 위한 병렬 가우스 과정)

  • Sin, Bong-Kee
    • Journal of KIISE
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    • v.42 no.6
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    • pp.748-754
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    • 2015
  • This paper proposes a sequential state estimation model consisting of continuous and discrete variables, as a way of generalizing all discrete-state factorial HMM, and gives a design of gait motion model based on the idea. The discrete state variable implements a Markov chain that models the gait dynamics, and for each state of the Markov chain, we created a Gaussian process over the space of the continuous variable. The Markov chain controls the switching among Gaussian processes, each of which models the rotation or various views of a gait state. Then a particle filter-based algorithm is presented to give an approximate filtering solution. Given an input vector sequence presented over time, this finds a trajectory that follows a Gaussian process and occasionally switches to another dynamically. Experimental results show that the proposed model can provide a very intuitive interpretation of video-based gait into a sequence of poses and a sequence of posture states.

A Semi-Markov Decision Process (SMDP) for Active State Control of A Heterogeneous Network

  • Yang, Janghoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.7
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    • pp.3171-3191
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    • 2016
  • Due to growing demand on wireless data traffic, a large number of different types of base stations (BSs) have been installed. However, space-time dependent wireless data traffic densities can result in a significant number of idle BSs, which implies the waste of power resources. To deal with this problem, we propose an active state control algorithm based on semi-Markov decision process (SMDP) for a heterogeneous network. A MDP in discrete time domain is formulated from continuous domain with some approximation. Suboptimal on-line learning algorithm with a random policy is proposed to solve the problem. We explicitly include coverage constraint so that active cells can provide the same signal to noise ratio (SNR) coverage with a targeted outage rate. Simulation results verify that the proposed algorithm properly controls the active state depending on traffic densities without increasing the number of handovers excessively while providing average user perceived rate (UPR) in a more power efficient way than a conventional algorithm.

A Stochastic Model for the Nuclide Migration in Geologic Media Using a Continuous Time Markov Process (연속시간 마코프 프로세스를 이용한 지하매질에서의 통계적 핵종이동 모델)

  • Lee, Y.M.;Kang, C.H.;Hahn, P.S.;Park, H.H.;Lee, K.J.
    • Nuclear Engineering and Technology
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    • v.25 no.1
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    • pp.154-165
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    • 1993
  • A stochastic method using continuous time Markov process is presented to model the one-dimensional convective nuclide transport in geologic media, which have usually heterogeneous feature in physical/geochemical parameters such as velocity, dispersion coefficient, and retardation factor resulting poor description by conventional deterministic advection-dispersion model. The primary desired quantities from a stochastic model are the mean values and variance of the state variables as a function of time. The time-dependent probability distributions of nuclides are presented for each discretized compartment given the volumetric groundwater flux and the intensity of transition. Since this model is discrete in medium space, physical/geochemical parameters which affect nuclide transport can be easily incorporated for the heterogeneous media as well as remarkably layered media having spatially varied parameters. Even though the Markov process model developed in this study was shown to be sensitive to the number of discretized compartments showing numerical dispersion as the number of compartments are increased, this could be easily calibrated by comparing with the analytical deterministic model.

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A Nuclide Transport Model in the Fractured Rock Medium Using a Continuous Time Markov Process (연속시간 마코프 프로세스를 이용한 균열암반매질에서의 핵종이동 모델)

  • Lee, Y.M.;Kang, C.H.;Hahn, P.S.;Park, H.H.;Lee, K.J.
    • Nuclear Engineering and Technology
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    • v.25 no.4
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    • pp.529-538
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    • 1993
  • A stochastic way using continuous time Markov process is presented to model the one-dimensional nuclide transport in fractured rock matrix as an extended study for previous work [1]. A nuclide migration model by the continuous time Markov process for single planar fractured rock matrix, which is considered as a transient system where a process by which the nuclide is diffused into the rock matrix from the fracture may be no more time homogeneous, is compared with a conventional deterministic analytical solution. The primary desired quantities from a stochastic model are the expected values and variance of the state variables as a function of time. The time-dependent probability distributions of nuclides are presented for each discretized compartment of the medium given intensities of transition. Since this model is discrete in medium space, parameters which affect nuclide transport could be easily incorporated for such heterogeneous media as the fractured rock matrix and the layered porous media. Even though the model developed in this study was shown to be sensitive to the number of discretized compartment showing numerical dispersion as the number of compartments are decreased, with small compensating of dispersion coefficient, the model agrees well to analytical solution.

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