• Title/Summary/Keyword: Markov chain model

Search Result 122, Processing Time 0.128 seconds

The Probabilistic Analysis of Fatigue Damage Accumulation Behavior Using Markov Chain Model in CFRP Composites (Markov Chain Model을 이용한 CFRP 복합재료의 피로손상누적거동에 대한 확률적 해석)

  • Kim, Do-Sik;Kim, In-Bai;Kim, Jung-Kyu
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.20 no.4
    • /
    • pp.1241-1250
    • /
    • 1996
  • The characteristics of fatigue cumulative damage and fatigue life of 8-harness satin woven CFRP composites with a circular hole under constant amplitude and 2-level block loading are estimated by Stochastic Makov chain model. It is found in this study that the fatigue damage accumulation behavior is very random and the fatigue damage is accumulated as two regions under constant amplitude fatigue loading. In constant amplitude fatigue loading the predicted mean number of cycles to a specified damage state by Markov chain model shows a good agreement with the test result. The predicted distribution of the fatigue cumulative damage by Markov chain model is similar to the test result. The fatigue life predictions under 2-level block loading by Markov chain model revised are good fitted to the test result more than by 2-parameter Weibull distribution function using percent failure rule.

Study on Demand Estimation of Agricultural Machinery by Using Logistic Curve Function and Markov Chain Model (로지스틱함수법 및 Markov 전이모형법을 이용한 농업기계의 수요예측에 관한 연구)

  • Yun Y. D.
    • Journal of Biosystems Engineering
    • /
    • v.29 no.5
    • /
    • pp.441-450
    • /
    • 2004
  • This study was performed to estimate mid and long term demands of a tractor, a rice transplanter, a combine and a grain dryer by using logistic curve function and Markov chain model. Field survey was done to decide some parameters far logistic curve function and Markov chain model. Ceiling values of tractor and combine fer logistic curve function analysis were 209,280 and 85,607 respectively. Based on logistic curve function analysis, total number of tractors increased slightly during the period analysed. New demand for combine was found to be zero. Markov chain analysis was carried out with 2 scenarios. With the scenario 1(rice price $10\%$ down and current supporting policy by government), new demand for tractor was decreased gradually up to 700 unit in the year 2012. For combine, new demand was zero. Regardless of scenarios, the replacement demand was increased slightly after 2003. After then, the replacement demand is decreased after the certain time. Two analysis of logistic owe function and Markov chain model showed the similar trend in increase and decrease for total number of tractors and combines. However, the difference in numbers of tractors and combines between the results from 2 analysis got bigger as the time passed.

A Probabilistic Analysis for Fatigue Cumulative Damage and Fatigue Life in CFRP Composites Containing a Circular Hole (원공을 가진 CFRP 복합재료의 피로누적손상 및 피로수명에 대한 확률적 해석)

  • 김정규;김도식
    • Transactions of the Korean Society of Mechanical Engineers
    • /
    • v.19 no.8
    • /
    • pp.1915-1926
    • /
    • 1995
  • The Fatigue characteristics of 8-harness satin woven CFRP composites with a circular hole are experimentally investigated under constant amplitude tension-tension loading. It is found in this study that the fatigue damage accumulation behavior is very random and history-independent, and the fatigue cumulative damage is linearly related with the mean number of cycles to a specified damage state. From these results, it is known that the fatigue characteristics of CFRP composites satisfy the basic assumptions of Markov chain theory and the parameter of Markov chain model can be determined only by mean and variance of fatigue lives. The predicted distribution of the fatigue cumulative damage using Markov chain model shows a good agreement with the test results. For the fatigue life distribution, Markov chain model makes similar accuracy to 2-parameter Weibull distribution function.

Performance analysis and saturation bound research of cyclic-quorum multichannel MAC protocol based on Markov chain model

  • Hu, Xing;Ma, Linhua;Huang, Shaocheng;Huang, Jinke;Sun, Kangning;Huang, Tianyu
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.11 no.8
    • /
    • pp.3862-3888
    • /
    • 2017
  • In high diversity node situation, single-channel MAC protocols suffer from many collisions. To solve this problem, the research of multichannel MAC protocol has become a hotspot. And the cyclic quorum-based multichannel (CQM) MAC protocol outperformed others owing to its high frequency utilization. In addition, it can avoid the bottleneck that others suffered from and can be easily realized with only one transceiver. To obtain the accurate performance of CQM MAC protocol, a Markov chain model, which combines the channel hopping strategy of CQM protocol and IEEE 802.11 distributed coordination function (DCF), is proposed. The metrics (throughput and average packet transmission delay) are calculated in performance analysis, with respect to node number, packet rate, channel slot length and channel number. The results of numerical analysis show that the optimal performance of CQM protocol can be obtained in saturation bound situation. And then we obtain the saturation bound of CQM system by bird swarm algorithm (BSA). Finally, the Markov chain model and saturation bound are verified by Qualnet platform. And the simulation results show that the analytic and simulation results match very well.

A study on Classification of Insider threat using Markov Chain Model

  • Kim, Dong-Wook;Hong, Sung-Sam;Han, Myung-Mook
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.12 no.4
    • /
    • pp.1887-1898
    • /
    • 2018
  • In this paper, a method to classify insider threat activity is introduced. The internal threats help detecting anomalous activity in the procedure performed by the user in an organization. When an anomalous value deviating from the overall behavior is displayed, we consider it as an inside threat for classification as an inside intimidator. To solve the situation, Markov Chain Model is employed. The Markov Chain Model shows the next state value through an arbitrary variable affected by the previous event. Similarly, the current activity can also be predicted based on the previous activity for the insider threat activity. A method was studied where the change items for such state are defined by a transition probability, and classified as detection of anomaly of the inside threat through values for a probability variable. We use the properties of the Markov chains to list the behavior of the user over time and to classify which state they belong to. Sequential data sets were generated according to the influence of n occurrences of Markov attribute and classified by machine learning algorithm. In the experiment, only 15% of the Cert: insider threat dataset was applied, and the result was 97% accuracy except for NaiveBayes. As a result of our research, it was confirmed that the Markov Chain Model can classify insider threats and can be fully utilized for user behavior classification.

A Study on the Fatigue Reliability of Structures by Markov Chain Model (Markov Chain Model을 이용한 구조물의 피로 신뢰성 해석에 관한 연구)

  • Y.S. Yang;J.H. Yoon
    • Journal of the Society of Naval Architects of Korea
    • /
    • v.28 no.2
    • /
    • pp.228-240
    • /
    • 1991
  • Many experimental data of fatigue crack propagation show that the fatigue crack propagation process is stochastic. Therefore, the study on the crack propagation must be based on the probabilistic approach. In the present paper, fatigue crack propagation process is assumed to be a discrete Markov process and the method is developed, which can evaluate the reliability of the structural component by using Markov chain model(Unit step B-model) suggested by Bogdanoff. In this method, leak failure, plastic collapse and brittle fracture of the critical component are taken as failure modes, and the effects of initial crack distribution, periodic and non-periodic inspection on the probability of failure are considered. In this method, an equivalent load value for random loading such as wave load is used to facilitate the analysis. Finally some calculations are carried out in order to show the usefulness and the applicability of this method. And then some remarks on this method are mentioned.

  • PDF

A Generalized Markov Chain Model for IEEE 802.11 Distributed Coordination Function

  • Zhong, Ping;Shi, Jianghong;Zhuang, Yuxiang;Chen, Huihuang;Hong, Xuemin
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.6 no.2
    • /
    • pp.664-682
    • /
    • 2012
  • To improve the accuracy and enhance the applicability of existing models, this paper proposes a generalized Markov chain model for IEEE 802.11 Distributed Coordination Function (DCF) under the widely adopted assumption of ideal transmission channel. The IEEE 802.11 DCF is modeled by a two dimensional Markov chain, which takes into account unsaturated traffic, backoff freezing, retry limits, the difference between maximum retransmission count and maximum backoff exponent, and limited buffer size based on the M/G/1/K queuing model. We show that existing models can be treated as special cases of the proposed generalized model. Furthermore, simulation results validate the accuracy of the proposed model.

Markov Model-Driven in Real-time Faulty Node Detection for Naval Distributed Control Networked Systems (마코브 연산 기반의 함정 분산 제어망을 위한 실시간 고장 노드 탐지 기법 연구)

  • Noh, Dong-Hee;Kim, Dong-Seong
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.20 no.11
    • /
    • pp.1131-1135
    • /
    • 2014
  • This paper proposes the enhanced faulty node detection scheme with hybrid algorithm using Markov-chain model on BCH (Bose-Chaudhuri-Hocquenghem) code in naval distributed control networked systems. The probabilistic model-driven approach, on Markov-chain model, in this paper uses the faulty weighting interval factors, which are based on the BCH code. In this scheme, the master node examines each slave-nodes continuously using three defined states : Good, Warning, Bad-state. These states change using the probabilistic calculation method. This method can improve the performance of detecting the faulty state node more efficiently. Simulation results show that the proposed method can improve the accuracy in faulty node detection scheme for real-time naval distributed control networked systems.

Development of Statistical Downscaling Model Using Nonstationary Markov Chain (비정상성 Markov Chain Model을 이용한 통계학적 Downscaling 기법 개발)

  • Kwon, Hyun-Han;Kim, Byung-Sik
    • Journal of Korea Water Resources Association
    • /
    • v.42 no.3
    • /
    • pp.213-225
    • /
    • 2009
  • A stationary Markov chain model is a stochastic process with the Markov property. Having the Markov property means that, given the present state, future states are independent of the past states. The Markov chain model has been widely used for water resources design as a main tool. A main assumption of the stationary Markov model is that statistical properties remain the same for all times. Hence, the stationary Markov chain model basically can not consider the changes of mean or variance. In this regard, a primary objective of this study is to develop a model which is able to make use of exogenous variables. The regression based link functions are employed to dynamically update model parameters given the exogenous variables, and the model parameters are estimated by canonical correlation analysis. The proposed model is applied to daily rainfall series at Seoul station having 46 years data from 1961 to 2006. The model shows a capability to reproduce daily and seasonal characteristics simultaneously. Therefore, the proposed model can be used as a short or mid-term prediction tool if elaborate GCM forecasts are used as a predictor. Also, the nonstationary Markov chain model can be applied to climate change studies if GCM based climate change scenarios are provided as inputs.