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Herbert DawidA Markov Chain Analysis of Genetic Algorithms with a State Dependent Fitness Function Complex Systems Vol.8,pp.407-417,1994

1996 Journal of Japan Society for Fuzzy Theory and Systems  
Markov Chains " ( Nix and Vose : Annals of Mathematics and Artificial Intelli − gence , 5,1992)に お け る モ デ ル の 基 本 記 述 を 用 い て い る .  ...  こ の 漸 近 安 定 条 件 は , そ の Homogeneous Stateで の 評 価 関 数値 と 交 叉 の 条 件 で 表 現 さ れ る .本 論 文 で は こ の 結 果 を 用 い て , 一 点 交 叉 , 一 様 交 叉 の 場 合 に お い て Homogeneous Statesが 漸 近 安 定に な る た め の 関 数 値 お よ び 交 叉 確率 の 条件  ... 
doi:10.3156/jfuzzy.8.2_245 fatcat:z6mjwws3cjecxipqop5uim5zpu

Page 6849 of Mathematical Reviews Vol. , Issue 94k [page]

1994 Mathematical Reviews  
The following type of process is considered: A semi-Markov pro- cess with countable state space generates rewards of a finite number of kinds.  ...  During a stay in each state, the rewards increase with a fixed state-dependent rate. At state transitions, the rewards may increase with a random transition-dependent jump.  ... 

Finding the probability distribution of states in the fuzzy markov systems

Lev Raskin, Oksana Sira, Tetiana Katkova
2017 Eastern-European Journal of Enterprise Technologies  
Analysis of Markov and semi-Markov systems with parameters that are not clearly assigned Let us examine a problem on finding the final distribution of probabilities of states of the Markov system whose  ...  However, these data make it possible to obtain the description in the terms of the theory of fuzzy sets with required quality. Principles of the theory of fuzzy sets are presented in [6] [7] [8] [9]  ...  Thus, the problem on finding the stationary distribution of probabilities of the EMC states is reduced to the following problem on mathematical programming: to find the set  ... 
doi:10.15587/1729-4061.2017.97144 fatcat:fcmbq43dbjgklmt5oq7mmcv44a

Fuzzy Markovian decision processes: Application to queueing systems

María José Pardo, David de la Fuente
2010 Computers and Mathematics with Applications  
To this end, first we have defined the theory linking Markov chains with non-fuzzy states with Markov chains with fuzzy states, and we have calculated the Markov chain probabilities with fuzzy states using  ...  In this paper, we calculate the best policy to be implemented regarding publicity decisions in a queueing system by using Markovian decision processes with fuzzy states.  ...  In Section 3 we have defined the theory linking Markov chains with non-fuzzy states with Markov chains with fuzzy states.  ... 
doi:10.1016/j.camwa.2010.08.004 fatcat:wshioo5u5nhfzodvowcylygfii

A Review of Risk Assessment Methods for Power System

Liang Zhao, Tianyang Mao, Wen Xu, Jingzhao Luan, Jiangning Wu, Guangyuan Qi, Bing Xu, Yinong Chen
2017 MATEC Web of Conferences  
Keywords .power system; risk assessment; analytic hierarchy process; Markov chain model; Monte Carlo method; fuzzy comprehensive evaluation 1 INTRODUCTION With the extensive application and popularization  ...  risk assessment, including the method of hierarchy analysis, Markov chain model, Monte Carlo method, fuzzy comprehensive evaluation and related research progress.  ...  Markov Chain Model Markov chain is a stochastic process of discrete events with Markovian properties in mathematics.  ... 
doi:10.1051/matecconf/201713900175 fatcat:cfjygamvpbgrhphlz56itvvgkq

Techniques for Dealing with Uncertainty in Cognitive Radio Networks [article]

Fatima Salahdine
2017 arXiv   pre-print
In the last step, uncertainty can affect the decision of the cognitive radio system, which sometimes can lead to the wrong action.  ...  This paper provides a deep overview of techniques that handle uncertainty in cognitive radio networks.  ...  The Hidden Markov model is a statistical Markov model [19] in which the modeled system is assumed to be a Markovian process with unobserved states.  ... 
arXiv:1701.05468v1 fatcat:tf5exhggrfbtfi3uiwzzakqjk4

Page 746 of Automation and Remote Control Vol. 34, Issue 5 [page]

1973 Automation and Remote Control  
Fuzzy Systems, Automata 4 system S with input x(t), output y(t), and state q(t) is called a fuzzy system if at least one of these variables is replaced by a fuzzy set [3].  ...  In [48] the author uses the theory of fuzzy algorithms to construct a fuzzy hierarchy of recursive functions that allows certain classes of recursive functions with a definite degree of fuzziness to be  ... 

Techniques for dealing with uncertainty in cognitive radio networks

Fatima Salahdine, Naima Kaabouch, Hassan El Ghazi
2017 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC)  
The Hidden Markov model is a statistical Markov model [19] in which the modeled system is assumed to be a Markovian process with unobserved states.  ...  It starts with a Markov chain and adds a noisy observation about the state at each time.  ... 
doi:10.1109/ccwc.2017.7868352 dblp:conf/ccwc/SalahdineKG17 fatcat:ueervetohrgptobxxgrmxfk4bm

Reliability Analysis of Relay Protection Based on the Fuzzy-Markov Model

Ganggang Hao, Huanxin Guan, Dongxue Qiu, Wei Du
2015 International Journal of Hybrid Information Technology  
This article considers the influence of the fuzzy uncertainty of relay protection failure rate to power system on the basis of Markov model, and researches the dynamic fault tree analysis method in the  ...  The triangular fuzzy numbers are used to express the failure rate of the components and system, after which the fuzzy Markov model has been established based on the dynamic fault tree model obtained before  ...  Acknowledgments This work is supported by National Nature Science Foundation of China under Grant 61304069, 61372195, 61371200, the Nature Science & Foundation of Liaoning Province under Grant 2013020124  ... 
doi:10.14257/ijhit.2015.8.10.11 fatcat:3g3ss3trpzbpzc4ucypja2gvpa

Multiyear Discrete Stochastic Programming with a Fuzzy Semi-Markov Process

C. S. Kim, Richard M. Adams, Dannele E. Peck
2016 Applied Mathematics  
One means of addressing these uncertainties is to re-cast drought as a stochastic, multiyear process using a "fuzzy" semi-Markov process.  ...  In this paper, we review "crisp" versus "fuzzy" representations of drought and show how fuzzy semi-Markov processes can aid researchers in developing more robust multiyear, discrete stochastic models.  ...  Acknowledgements The views expressed are those of the authors and should not be attributed to USDA or Economic Research Service.  ... 
doi:10.4236/am.2016.76044 fatcat:btetgxbf6fdifdvp3mm4smzmja

Evaluating the reliability of prototype degradable systems

M.L. Leuschen, I.D. Walker, J.R. Cavallaro
2001 Reliability Engineering & System Safety  
This paper develops fuzzy Markov modeling and uses it to analyze a speci®c robot designed for hazardous waste removal and speci®c types of electronic systems. q  ...  The technique introduced here is a logical extension of the underlying concepts of fuzzy sets and Markov models.  ...  Fuzzy Markov modeling of a RAID system In an effort to demonstrate the wider applicability of fuzzy Markov modeling, we will now apply it to a RAID 5 system.  ... 
doi:10.1016/s0951-8320(00)00097-1 fatcat:mcpji7acpzdlnmmqvmbs67mlv4

Page 6542 of Mathematical Reviews Vol. , Issue 99i [page]

1999 Mathematical Reviews  
If the system is in a given state and the controller decides a certain action, then the state of the system at the beginning of the following slot is gov- erned by a Markov-like transition probability  ...  A resolvent equation, well known in Markov potential theory, is proposed, regarding the fuzzy transition from a viewpoint of possibility theory.  ... 

A Fuzzy Markov Model for Risk and Reliability Prediction of Engineering Systems: A Case Study of a Subsea Wellhead Connector

Nan Pang, Peng Jia, Peilin Liu, Feng Yin, Lei Zhou, Liquan Wang, Feihong Yun, Xiangyu Wang
2020 Applied Sciences  
Based on the fault tree, fuzzy comprehensive evaluation and Markov method, this paper proposed a fuzzy Markov method that takes the full advantages of the three methods and makes the analysis of risk,  ...  This method uses the fault tree and fuzzy theory to preprocess the input failure data to improve the reliability of the input failure data, and then input the preprocessed failure data into the Markov  ...  Conflicts of Interest: The authors declare no conflicts of interest.  ... 
doi:10.3390/app10196902 fatcat:beelsdwlevhr7hfxha4w5ilv3u

Page 2081 of Mathematical Reviews Vol. , Issue 84e [page]

1984 Mathematical Reviews  
systems with aftereffect, and with the construction and study of Markov models for such systems.  ...  Authors’ summary: “We deal with the applications of probabilistic sets in system theory, especially in system identification and the design of fuzzy logic controllers.  ... 

Fuzzy Reliability Assessment of Safety Instrumented Systems Accounting for Common Cause Failure

Hongping Yu, Yue Zhao, Li Mo
2020 IEEE Access  
Ding and Lisnianski [31] introduced the fuzzy multi-state system. Liu and Huang [32] evaluated the fuzzy reliability of fuzzy multi-state elements and systems based on fuzzy Markov models.  ...  Various theories have been introduced to deal with epistemic uncertainty, including probability-box [13] [15] , interval theory [16] , [17] possibility theory [18] , fuzzy set theory [19] , [20  ...  (3, 4) () pt . 4.8) , the fuzzy transition intensity of Component #1 transiting from State 3 to State 2 is (4.26 6.4 9.6) based on the arithmetical operations of fuzzy numbers.  ... 
doi:10.1109/access.2020.3010878 fatcat:ewkfrecm4ngmhiubmgzdr4q7ia
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