• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.488-488
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• 2015

Intermittent streamflow is common phenomenon in arid and semi-arid regions. To manage water resources of intermittent streamflows, stochactic simulation data is essential; however the seasonally stochastic modeling for intermittent streamflow is a difficult task. In this study, using the periodic Markov chain model, we simulate intermittent monthly streamflow for occurrence and the periodic gamma autoregressive and copula models for amount. The copula models were tested in a previous study for the simulation of yearly streamflow, resulting in successful replication of the key and operational statistics of historical data; however, the copula models have never been tested on a monthly time scale. The intermittent models were applied to the Colorado River system in the present study. A few drawbacks of the PGAR model were identified, such as significant underestimation of minimum values on an aggregated yearly time scale and restrictions of the parameter boundaries. Conversely, the copula models do not present such drawbacks but show feasible reproduction of key and operational statistics. We concluded that the periodic Markov chain based the copula models is a practicable method to simulate intermittent monthly streamflow time series.

• ETRI Journal
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• v.45 no.3
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• pp.394-403
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• 2023

Direct tracking problem of moving noncircular sources for multiple arrays is investigated in this study. Here, we propose an improved unscented particle filter (I-UPF) direct tracking method, which combines system proportional symmetry unscented particle filter and Markov Chain Monte Carlo (MCMC) algorithm. Noncircular sources can extend the dimension of sources matrix, and the direct tracking accuracy is improved. This method uses multiple arrays to receive sources. Firstly, set up a direct tracking model through consecutive time and Doppler information. Subsequently, based on the improved unscented particle filter algorithm, the proposed tracking model is to improve the direct tracking accuracy and reduce computational complexity. Simulation results show that the proposed improved unscented particle filter algorithm for noncircular sources has enhanced tracking accuracy than Markov Chain Monte Carlo unscented particle filter algorithm, Markov Chain Monte Carlo extended Kalman particle filter, and two-step tracking method.

• Journal of applied mathematics & informatics
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• v.30 no.3_4
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• pp.541-553
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• 2012

In this paper, we study some limit properties of the harmonic mean of random transition probability for a second-order nonhomogeneous Markov chain on the generalized gambling system indexed by a tree by constructing a nonnegative martingale. As corollary, we obtain the property of the harmonic mean and the arithmetic mean of random transition probability for a second-order nonhomogeneous Markov chain indexed by a double root tree.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2452-2457
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• 2012

When a quality inspection process rejects a product unit, consecutive repeated inspections are sometimes conducted for the rejected unit to reduce a false reject possibility. This paper analyzes a special inspection process that allows up to two times of consecutive testing for each product to decrease type I inspection errors. This study uses a Markov chain to model the steps of the inspection process and a product unit's quality states during inspection. Historical inspection results from a company are used as the data for the Markov chain model. Using the Markov chain model and data, this study analyzes the effect of this special inspection rule on the proportion of the final quality levels and scrap rate. The results demonstrate that this inspection process of possible double testing could help reduce unnecessary rejects and consequently decrease material and production costs.

• Journal of Information Management
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• v.20 no.1
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• pp.66-85
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• 1989

The purpose of this study is to verify the following two hypotheses by using a test collection of 3.815 documents on the subject of chemistry. First hypothesis is that a Markov chain model can be used t9 describe and predict authors' movements among subareas of a discipline. Second hypothesis is that a transition matrix of the Markov chain can be applied to describ the intellectual structure of a discipline en the multidimensional space. The results of this study have shown that the Markov chain is a good model to be used to study the movement of korean chemists in 7 subtopics in chemistry and understand the intellectual structure of chemistry.

• International Journal of Contents
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• v.13 no.4
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• pp.80-87
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• 2017

Since the advent of the Internet, and the development of smart devices, people have begun to spend more time in online platforms; this phenomenon has created a large number of online Words of Mouth (WOM) daily. Under these changes, one of the important aspects to consider is the conformity effect in online WOM; that is, whether an individual's own opinion would be influenced by the majority opinion of other people. This study, therefore, investigates whether there is the conformity effect in online product ratings for Amazon.com using the method called Markov Chain analysis. Markov Chain analysis considers the stochastic process that satisfies the Markov property, and we assume that the generation of online product ratings follows the process. Under the assumption that people are usually independent when they express their opinion in online platforms, we analyze the interdependency among rating sequences, and we find weak evidence that there exists the conformity effect in online product rating. This suggests that people who leave online product ratings consider others' opinions.

• International Journal of Highway Engineering
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• v.4 no.4 s.14
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• pp.1-12
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• 2002

Pavement Management System has a special purpose that the rehabilitation strategy applied on pavement should be executable in view of technical and economical point after new pavement open to the traffic. To achieve that purpose, a reliable pavement performance prediction model should be embeded in the system. The object of this study is to develop a probabilistic pavement performance prediction model for evaluating asphalt pavements based on the Markov chain concept. In this paper, methodology of the Markov chain modeling principle is explained, and the application of this model to asphalt pavement is described. As the results, transition matrics for predicting asphalt pavement performance are obtained, and also performance life is estimated quantitatively by this system.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.28-34
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• 2021

Internet Service Providers (ISPs) constantly endeavor to resolve network congestion, in order to provide fast and cheap services to the customers. This study suggests two models based on Markov chain, using three and four access attempts to complete the call. It involves a comparative study of four models to check the relationship between Internet Access sharing traffic, and the possibility of network jamming. The first model is a Markov chain, based on call-by-call attempt, whereas the second is based on two attempts. Models III&IV suggested by the authors are based on the assumption of three and four attempts. The assessment reveals that sometimes by increasing the number of attempts for the same operator, the chances for the customers to complete the call, is also increased due to blocking probabilities. Three and four attempts express the actual relationship between traffic sharing and blocking probability based on Markov using MATLAB tools with initial probability values. The study reflects shouting results compared to I&II models using one and two attempts. The success ratio of the first model is 84.5%, and that of the second is 90.6% to complete the call, whereas models using three and four attempts have 94.95% and 95.12% respectively to complete the call.

• Communications of the Korean Mathematical Society
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• v.10 no.4
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• pp.975-980
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• 1995

We suggest an improvement of the algorithm in [2] for calculating the transient solutions for continuous time Markov chain with countable state space.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.3
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• pp.523-534
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• 1994

The purpose of this study is to develop computer simulation model that produce precipitation patterns from stochastic model. In the paper(I) of this study, the alternate renewal process(ARP) is used for the daily precipitation series. In this paper(Il), stochastic simulation models for the daily precipitation series are developed by combining Markov chain for the precipitation occurrence process and continuous probability distribution for the precipitation amounts on the wet days. The precipitation occurrence is determined by first order Markov chain with two states(dry and wet). The amounts of precipitation, given that precipitation has occurred, are described by a Gamma, Pearson Type-III, Extremal Type-III, and 3 parameter Weibull distribution. Since the daily precipitation series shows seasonal variation, models are identified for each month of the year separately. To illustrate the application of the simulation models, daily precipitation data were taken from records at the seven locations of the Nakdong and Seomjin river basin. Simulated data were similar to actual data in terms of distribution for wet and dry spells, seasonal variability, and precipitation amounts.