• Title/Summary/Keyword: Markov

Search Result 2,422, Processing Time 0.028 seconds

The Bus Delay Time Prediction Using Markov Chain (Markov Chain을 이용한 버스지체시간 예측)

  • Lee, Seung-Hun;Moon, Byeong-Sup;Park, Bum-Jin
    • The Journal of The Korea Institute of Intelligent Transport Systems
    • /
    • v.8 no.3
    • /
    • pp.1-10
    • /
    • 2009
  • Bus delay time is occurred as the result of traffic condition and important factor to predict bus arrival time. In this paper, transition probability matrixes between bus stops are made by using Markov Chain and it is predicted bus delay time with them. As the results of study, it is confirmed a possibility of adapting the assumption which it has same bus transition probability between stops through paired-samples T-test and overcame the limitation of exiting studies in case there is no scheduled bus arrival time for each stops with using bus interval time. Therefore it will be possible to predict bus arrival time with Markov Chain.

  • PDF

Hardware and Software Dependability Analysis of Embedded AVTMR(All Voting Triple Modular Redundancy) System (내장형 AVTMR 시스템의 하드웨어 및 소프트웨어 신뢰성 분석)

  • Kim, Hyun-Ki
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.34 no.7B
    • /
    • pp.744-750
    • /
    • 2009
  • In this paper, the unified Markov modeling of hardware and software for AVTMR(AlI Voting Triple Modular Redundancy) system is proposed and the dependability is analyzed. In hardware case, a failure rate is fixed to no time varying parameter. But, in software case, failure rate is applied with time varying parameter. Especially, the dependability(Reliability, Availability, Maintainability, Safety) of software is analyzed with G-O/NHPP for Markov modeling. The dependability of single and AVTMR system is analyzed and simulated with a unified Markov modeling method, and the characteristic of each system is compared accroding to failure rate. This kind of fault tolerat system can be applied to an airplane and life critical system to meet the requirement for a specific requirement.

Hand Gesture Recognition Using HMM(Hidden Markov Model) (HMM(Hidden Markov Model)을 이용한 핸드 제스처인식)

  • Ha, Jeong-Yo;Lee, Min-Ho;Choi, Hyung-Il
    • Journal of Digital Contents Society
    • /
    • v.10 no.2
    • /
    • pp.291-298
    • /
    • 2009
  • In this paper we proposed a vision based realtime hand gesture recognition method. To extract skin color, we translate RGB color space into YCbCr color space and use CbCr color for the final extraction. To find the center of extracted hand region we apply practical center point extraction algorithm. We use Kalman filter to tracking hand region and use HMM(Hidden Markov Model) algorithm (learning 6 type of hand gesture image) to recognize it. We demonstrated the effectiveness of our algorithm by some experiments.

  • PDF

Application of the Modified CA-Markov Technique for Future Prediction of Forest Land Cover in a Mountainous Watershed (미래 산림식생변화 예측을 위한 개선된 CA-Markov 기법의 적용)

  • Park, Min-Ji;Park, Geun-Ae;Lee, Yong-Jun;Kim, Seong-Joon
    • Journal of The Korean Society of Agricultural Engineers
    • /
    • v.52 no.1
    • /
    • pp.61-68
    • /
    • 2010
  • 토지피복은 대부분의 수문 수질 모형의 중요한 매개변수로서, 수자원 변화 예측에 중요한 입력자료로 활용되고 있다. 본 연구에서는 개선된 CA (Cellular Automata)-Markov 기법을 이용하여 충주댐유역의 미래 산림식생변화에 대한 예측을 시도하였다. 예측과정으로 과거의 Landsat TM 영상 (1985, 1990, 1995, 2000)을 이용하여 기법의 정확도 검증 및 산림분포의 변화경향을 파악하고, Landsat 산림은 2000년과 2005년의 NOAA AVHRR NDVI값을 기준으로 침엽수림, 혼효림, 활엽수림의 3종으로 구분한 후, 이를 이용하여 2030년, 2060년, 2090년의 식생변화를 추정하는 방법을 제안하였다. 이 방법의 적용결과, 2000년과 비교하여 2090년의 활엽수림과 혼효림은 각각 14.3 %, 11.6 % 증가하였으며, 침엽수림은 24.9 % 감소하는 것으로 나타났다. 과거의 경향성에 의해 예측을 시도한 본 연구결과는 미래 토지피복 변화에 따른 수문 수질 영향 분석시 지표 조건의 불확실성을 줄이는데 활용될 수 있다고 판단된다.

Application of GTH-like algorithm to Markov modulated Brownian motion with jumps

  • Hong, Sung-Chul;Ahn, Soohan
    • Communications for Statistical Applications and Methods
    • /
    • v.28 no.5
    • /
    • pp.477-491
    • /
    • 2021
  • The Markov modulated Brownian motion is a substantial generalization of the classical Brownian Motion. On the other hand, the Markovian arrival process (MAP) is a point process whose family is dense for any stochastic point process and is used to approximate complex stochastic counting processes. In this paper, we consider a superposition of the Markov modulated Brownian motion (MMBM) and the Markovian arrival process of jumps which are distributed as the bilateral ph-type distribution, the class of which is also dense in the space of distribution functions defined on the whole real line. In the model, we assume that the inter-arrival times of the MAP depend on the underlying Markov process of the MMBM. One of the subjects of this paper is introducing how to obtain the first passage probabilities of the superposed process using a stochastic doubling algorithm designed for getting the minimal solution of a nonsymmetric algebraic Riccatti equation. The other is to provide eigenvalue and eigenvector results on the superposed process to make it possible to apply the GTH-like algorithm, which improves the accuracy of the doubling algorithm.

State Encoding of Hidden Markov Linear Prediction Models

  • Krishnamurthy, Vikram;Poor, H.Vincent
    • Journal of Communications and Networks
    • /
    • v.1 no.3
    • /
    • pp.153-157
    • /
    • 1999
  • In this paper, we derive finite-dimensional non-linear fil-ters for optimally reconstructing speech signals in Switched Predic-tion vocoders, Code Excited Linear Prediction(CELP) and Differ-ential Pulse Code Modulation (DPCM). Our filter is an extension of the Hidden Markov filter.

  • PDF

Valuation of American Option Prices Under the Double Exponential Jump Diffusion Model with a Markov Chain Approximation (이중 지수 점프확산 모형하에서의 마코브 체인을 이용한 아메리칸 옵션 가격 측정)

  • Han, Gyu-Sik
    • Journal of Korean Institute of Industrial Engineers
    • /
    • v.38 no.4
    • /
    • pp.249-253
    • /
    • 2012
  • This paper suggests a numerical method for valuation of American options under the Kou model (double exponential jump diffusion model). The method is based on approximation of underlying asset price using a finite-state, time-homogeneous Markov chain. We examine the effectiveness of the proposed method with simulation results, which are compared with those from the conventional numerical method, the finite difference method for PIDE (partial integro-differential equation).

On the Starvation Period of CDF-Based Scheduling over Markov Time-Varying Channels

  • Kim, Yoora
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.41 no.8
    • /
    • pp.924-927
    • /
    • 2016
  • In this paper, we consider a cumulative distribution function (CDF)-based opportunistic scheduling for downlink transmission in a cellular network consisting of a base station and multiple mobile stations. We present a closed-form formula for the average starvation period of each mobile station (i.e., the length of the time interval between two successive scheduling points of a mobile station) over Markov time-varying channels. Based on our formula, we investigate the starvation period of the CDF-based scheduling for various system parameters.

Forecasting Probability of Precipitation Using Morkov Logistic Regression Model

  • Park, Jeong-Soo;Kim, Yun-Seon
    • Communications for Statistical Applications and Methods
    • /
    • v.14 no.1
    • /
    • pp.1-9
    • /
    • 2007
  • A three-state Markov logistic regression model is suggested to forecast the probability of tomorrow's precipitation based on the current meteorological situation. The suggested model turns out to be better than Markov regression model in the sense of the mean squared error of forecasting for the rainfall data of Seoul area.

Markov Chain Method for Monitoring Several Correlated Quality Characteristics with Variable Sampling Intervals

  • Chang, Duk-Joon
    • Journal of Korean Society for Quality Management
    • /
    • v.25 no.3
    • /
    • pp.39-50
    • /
    • 1997
  • Markov chain method to evaluate the properties of control charts with variable sampling intervals(VSI0 for simultaneously monitoring several correlated quality characteristics under multivariate normal process are investigated. For comparing the efficiencies and properties of multivariate control charts, we consider multivariate Shewhart, CUSUM and EWMA charts in terms of average time to signal(ATS) and average number of samples to signal(ANSS). We obtained stabilized numerical results with Markov chain method when the number of transient state is greater than 100.

  • PDF