• Title/Summary/Keyword: Markov-chain

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An Analysis on the Optimal Level of the Maintenance Float Using Absorbing Markov Chain (흡수 마코프 체인을 활용한 적정 M/F 재고 수준에 관한 연구)

  • Kim, Yong;Yoon, Bong-Kyoo
    • Journal of the military operations research society of Korea
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    • v.34 no.2
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    • pp.163-174
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    • 2008
  • The military is an organization where reliability and availability take much more importance than in any other organization. And, in line with a recent trend of putting emphasis on 'system readiness', not only functions but also availability of a weapon system has become one of achievement targets. In this regard, the military keeps spares for important facility and equipment, which is called as Maintenance Float (M/F), in order to enhance reliability and availability in case of an unforeseen event. The military has calculated yearly M/F requirements based on the number of equipment and utilization rate. However, this method of calculation has failed to meet the intended targets of reliability and availability due to lack of consideration on the characteristics of equipment malfunctions and maintenance unit's capability. In this research, we present an analysis model that can be used to determine an optimal M/F inventory level based on queuing and absorbed Markov chain theories. And, we applied the new analysis model to come out with an optimal volume of K-1 tank M/F for the OO division, which serves as counterattack military unit. In our view, this research is valuable because, while using more tractable methodology compared to previous research, we present a new analysis model that can describe decision making process on M/F level more satisfactorily.

Statistical Calibration and Validation of Mathematical Model to Predict Motion of Paper Helicopter (종이 헬리콥터 낙하해석모델의 통계적 교정 및 검증)

  • Kim, Gil Young;Yoo, Sung Bum;Kim, Dong Young;Kim, Dong Seong;Choi, Joo Ho
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.39 no.8
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    • pp.751-758
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    • 2015
  • Mathematical models are actively used to reduce the experimental expenses required to understand physical phenomena. However, they are different from real phenomena because of assumptions or uncertain parameters. In this study, we present a calibration and validation method using a paper helicopter and statistical methods to quantify the uncertainty. The data from the experiment using three nominally identical paper helicopters consist of different groups, and are used to calibrate the drag coefficient, which is an unknown input parameter in both analytical models. We predict the predicted fall time data using probability distributions. We validate the analysis models by comparing the predicted distribution and the experimental data distribution. Moreover, we quantify the uncertainty using the Markov Chain Monte Carlo method. In addition, we compare the manufacturing error and experimental error obtained from the fall-time data using Analysis of Variance. As a result, all of the paper helicopters are treated as one identical model.

Prediction of Urban Land Cover Change Using Multilayer Perceptron and Markov Chain Analysis (다층 퍼셉트론(MLP)과 마코프 체인 분석(MCA)을 이용한 도심지 피복 변화 예측)

  • Bhang, Kon Joon;Sarker, Tanni;Lee, Jin-Duk
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.2
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    • pp.85-94
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    • 2018
  • The change of land covers in 2026 was prediceted based on the change of urbanization in 1996, 2006 and 2016 in Seoul and surrounding areas in this study. Landsat images were used as the basic data, and MLP (Multilayer Perceptron) and MCA (Markov Chain Analysis) were integrated for future prediction for the study area. The land cover transition potentials were calculated by setting up sub-models in MLP and the driving factors of land cover transition from 1996 to 2006 and transition probabilities were calculated using MCA to generate the land cover map of 2016. This was compared to the land cover map of 2016 from Landsat. MLP and MCA were verified and the future land covers of 2026 were predicted using the land cover map from Landsat in 2006 and 2016. As a result, it was predicted that the major land cover changes from 1996 to 2006 were from Barren Land and Grass Land to Builtup Area, and the same trend of transition will be remained for 2026. This study is meaningful in that it is applied for the first time to predict the future coating change in Seoul and surrounding areas by the MLP-MCA method.

The Analysis of Forest Successional Trend by Species Replacement Model in the Natural Forest (천연림의 수종 대치 작용 모델에 의한 산림천이 경향 분석)

  • 김지홍
    • Journal of Korea Foresty Energy
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    • v.22 no.3
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    • pp.1-10
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    • 2003
  • The successional status and potential natural vegetation were examined in the natural deciduous forest in Mt. Chombong area. The examination was based on the subsequent process of generation replacement by understory saplings for the dominant canopy trees within 106 20mx20m square sample plots. The transition matrix model, which was modified from mathematical theory of Markov chain, was employed to analyze the successional status of the study forest. The model suggests that study forest is still seral, and it is considered to be more than 500 years away from the steady state or climax in terms of species composition. The simulations predict a remarkable decrease in the proportion of species composition of the present dominant Quercus mongolica and Kalopanax pictus from current 42.6% and 8.1% to less than 13.3% and 0.5%, respectively, at the steady state. On the contrary, the proportions of Abies holophylla, Acer mono, Fraxinus mandshurica, Tilia amurensis, and Acer pseudo-sieboldianum will increase at the steady state. The change of predicted composition ratio was generally coincide with the result of tolerance index to be compared with the study model. The hypothesis and sensitivity of the model were also discussed to evaluate the applicability to the real situation. The overall results indicated that the present dynamics of the forest must reflect the seral state due to previous disturbance mainly by human related interference.

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An Impact Assessment of Climate and Landuse Change on Water Resources in the Han River (기후변화와 토지피복변화를 고려한 한강 유역의 수자원 영향 평가)

  • Kim, Byung-Sik;Kim, Soo-Jun;Kim, Hung-Soo;Jun, Hwan-Don
    • Journal of Korea Water Resources Association
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    • v.43 no.3
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    • pp.309-323
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    • 2010
  • As climate changes and abnormal climates have drawn research interest recently, many countries utilize the GCM, which is based on SRES suggested by IPCC, to obtain more accurate forecast for future climate changes. Especially, many research attempts have been made to simulate localized geographical characteristics by using RCM with the high resolution data globally. To evaluate the impacts of climate and landuse change on water resources in the Han-river basin, we carried out the procedure consisting of the CA-Markov Chain, the Multi-Regression equation using two independent variables of temperature and rainfall, the downscaling technique based on the RegCM3 RCM, and SLURP. From the CA-Markov Chain, the future landuse change is forecasted and the future NDVI is predicted by the Multi-Regression equation. Also, RegCM3 RCM 50 sets were generated by the downscaling technique based on the RegCM3 RCM provided by KMA. With them, 90 year runoff scenarios whose period is from 2001 to 2090 are simulated for the Han-river basin by SLURP. Finally, the 90-year simulated monthly runoffs are compared with the historical monthly runoffs for each dam in the basin. At Paldang dam, the runoffs in September show higher increase than the ones in August which is due to the change of rainfall pattern in future. Additionally, after exploring the impact of the climate change on the structure of water circulation, we find that water management will become more difficult by the changes in the water circulation factors such as precipitation, evaporation, transpiration, and runoff in the Han-river basin.

Inferring transmission routes of avian influenza during the H5N8 outbreak of South Korea in 2014 using epidemiological and genetic data (역학과 유전학적 데이터를 이용한 한국에서 2014년 발생한 H5N8 조류독감 전염경로의 유추)

  • Choi, Sang Chul
    • Korean Journal of Microbiology
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    • v.54 no.3
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    • pp.254-265
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    • 2018
  • Avian influenza recently damaged the poultry industry, which suffered a huge economic loss reaching billions of U.S. dollars in South Korea. Transmission routes of the pathogens would help plan to control and limit the spread of the devastating biological tragedy. Phylogenetic analyses of pathogen's DNA sequences could sketch transmission trees relating hosts with directed edges. The last decade has seen the methodological development of inferring transmission trees using epidemiological as well as genetic data. Here, I reanalyzed the DNA sequence data that had originated in the highly pathogenic avian influenza H5N8 outbreak of South Korea in 2014. The H5N8 viruses spread geographically contiguously from the origin of the outbreak, Jeonbuk. The Jeonbuk origin viruses were known to spread to four provinces neighboring Jeonbuk. I estimated the transmission tree of the host domestic and migratory wild birds after combining multiple runs of Markov chain Monte Carlo using a Bayesian method for inferring transmission trees. The estimated transmission tree, albeit with a rather large uncertainty in the directed edges, showed that the viruses spread from Jeonbuk through Chungnam to Gyeonggi. Domestic birds of breeder or broiler ducks were estimated to appear to be at the terminal nodes of the transmission tree. This observation confirmed that migratory wild birds played an important role as one of the main infection mediators in the avian influenza H5N8 outbreak of South Korea in 2014.

A Markov Chain Model for Population Distribution Prediction Considering Spatio-Temporal Characteristics by Migration Factors (이동요인별 시·공간적 인구이동 특성을 고려한 인구분포 예측: 마르코프 연쇄 모형을 활용하여)

  • Park, So Hyun;Lee, Keumsook
    • Journal of the Economic Geographical Society of Korea
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    • v.22 no.3
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    • pp.351-365
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    • 2019
  • This study aims to predict the changes in population distribution in Korea by considering spatio-temporal characteristics of major migration reasons. For the purpose, we analyze the spatio-temporal characteristics of each major migration reason(such as job, family, housing, and education) and estimate the transition probability, respectively. By appling Markov chain model processes with the ChapmanKolmogorov equation based on the transition probability, we predict the changes in the population distribution for the next six years. As the results, we found that there were differences of population changes by regions, while there were geographic movements into metropolitan areas and cities in general. The methodologies and the results presented in this study can be utilized for the provision of customized planning policies. In the long run, it can be used as a basis for planning and enforcing regionally tailored policies that strengthen inflow factors and improve outflow factors based on the trends of population inflow and outflow by region by movement factors as well as identify the patterns of population inflow and outflow in each region and predict future population volatility.

Development of methodology for daily rainfall simulation considering distribution of rainfall events in each duration (강우사상의 지속기간별 분포 특성을 고려한 일강우 모의 기법 개발)

  • Jung, Jaewon;Kim, Soojun;Kim, Hung Soo
    • Journal of Korea Water Resources Association
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    • v.52 no.2
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    • pp.141-148
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    • 2019
  • When simulating the daily rainfall amount by existing Markov Chain model, it is general to simulate the rainfall occurrence and to estimate the rainfall amount randomly from the distribution which is similar to the daily rainfall distribution characteristic using Monte Carlo simulation. At this time, there is a limitation that the characteristics of rainfall intensity and distribution by time according to the rainfall duration are not reflected in the results. In this study, 1-day, 2-day, 3-day, 4-day rainfall event are classified, and the rainfall amount is estimated by rainfall duration. In other words, the distributions of the total amount of rainfall event by the duration are set using the Kernel Density Estimation (KDE), the daily rainfall in each day are estimated from the distribution of each duration. Total rainfall amount determined for each event are divided into each daily rainfall considering the type of daily distribution of the rainfall event which has most similar rainfall amount of the observed rainfall using the k-Nearest Neighbor algorithm (KNN). This study is to develop the limitation of the existing rainfall estimation method, and it is expected that this results can use for the future rainfall estimation and as the primary data in water resource design.

Seismic Reliability Analysis of Offshore Wind Turbine with Twisted Tripod Support using Subset Simulation Method (부분집합 시뮬레이션 방법을 이용한 꼬인 삼각대 지지구조를 갖는 해상풍력발전기의 지진 신뢰성 해석)

  • Park, Kwang-Yeun;Park, Wonsuk
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.32 no.2
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    • pp.125-132
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    • 2019
  • This paper presents a seismic reliability analysis method for an offshore wind turbine with a twisted tripod support structure under earthquake loading. A three dimensional dynamic finite element model is proposed to consider the nonlinearity of the ground-pile interactions and the geometrical characteristics of the twisted tripod support structure where out-of-plane displacement occurs even under in-plane lateral loadings. For the evaluation of seismic reliability, the failure probability was calculated for the maximum horizontal displacement of the pile head, which is calculated from time history analysis using artificial earthquakes for the design return periods. The application of the subset simulation method using the Markov Chain Monte Carlo(MCMC) sampling is proposed for efficient reliability analysis considering the limit state equation evaluation by the nonlinear time history analysis. The proposed method can be applied to the reliability evaluation and design criteria development of the offshore wind turbine with twisted tripod support structure in which two dimensional models and static analysis can not produce accurate results.

A Method for Group Mobility Model Construction and Model Representation from Positioning Data Set Using GPGPU (GPGPU에 기반하는 위치 정보 집합에서 집단 이동성 모델의 도출 기법과 그 표현 기법)

  • Song, Ha Yoon;Kim, Dong Yup
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.3
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    • pp.141-148
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    • 2017
  • The current advancement of mobile devices enables users to collect a sequence of user positions by use of the positioning technology and thus the related research regarding positioning or location information are quite arising. An individual mobility model based on positioning data and time data are already established while group mobility model is not done yet. In this research, group mobility model, an extension of individual mobility model, and the process of establishment of group mobility model will be studied. Based on the previous research of group mobility model from two individual mobility model, a group mobility model with more than two individual model has been established and the transition pattern of the model is represented by Markov chain. In consideration of real application, the computing time to establish group mobility mode from huge positioning data has been drastically improved by use of GPGPU comparing to the use of traditional multicore systems.