Optimal energy efficiency routing strategy based on community in mobile social network by Ying PENG, Nao WANG, Gao-cai WANG

“…An optimal energy efficiency routing strategy based on community was proposed,which minimized the network energy consumption under the given delay constraint.Firstly the expected energy consumption and delay of message delivery in the connected network were obtained through Markov chain.Then the comprehensive cost function for delivering message from source node to destination node was designed,which was combined with energy consumption and delay.Thus,the optimization function to comprehensive cost of relay node delivering message was obtained,and further the reward function of relay node was gotten.Finally the optimal expected reward of optimal relay node was achieved using the optimal stopping theory,so as to realize the optimal energy efficiency routing strategy.In simulations,the average energy consumption,the average delay and the average delivery ratio of routing optimization strategy were compared with those of other routing strategies in related literatures.The results show that the strategy proposed has smaller average energy consumption,shorter average delay and higher average delivery ratio,gaining better energy consumption optimization effect.…”
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Optimal Maneuver Strategy of Observer for Bearing-Only Tracking in Threat Environment by Renke He, Shuxin Chen, Hao Wu, Zhuowei Liu, Jianhua Chen

“…The quantization method was used to discretize the BOT process and calculate the transition matrix of Markov chain; to achieve quantization in the beginning of each period, CKF was applied to provide the initial state estimate and the corresponding error covariance. …”
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Splitting Travel Time Based on AFC Data: Estimating Walking, Waiting, Transfer, and In-Vehicle Travel Times in Metro System by Yong-Sheng Zhang, En-Jian Yao

“…A new estimation model based on Bayesian inference formulation is proposed in this paper by integrating the probability measurement of the OD pair with only one effective route, in which all kinds of times follow the truncated normal distributions. Then, Markov Chain Monte Carlo method is designed to estimate all parameters endogenously. …”
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BeiDou satellites cross-regional communication path assignment model and resource management by Sheng Liu, Di Wu, Lanyong Zhang

“…Therefore, in this study, we develop a path assignment model based on the idea of clustering and Markov chain. The optimal path is determined by the objective function based on the maximum transition probability. …”
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Cooperative MAC protocol based on network coding and space-time coding by Qian-bin CHEN, Jian LIU, Yong FENG, Lun TANG

“…Aiming at the problems in wireless ad hoc networks,such as relays’ low efficiency caused by cooperation and difficult to meet the different QoS requirements,a co e MAC protocol was proposed based on the combination of network coding and space-time coding(NSTCMAC).Based on NSTCMAC protocol with the combination of Network coding and space-time coding techniques,a kind of cooperative MAC transmission mechanism that could distinguish the type of DATA packet was designed in order to meet the QoS requirements of different types of transm Further more,cooperative transmission mechanism and its performance were analyzed through Markov chain model.When transmitting the non-real-time(NR) packets,network coding was adopted to improve the efficiency of relay nodes; when transmitting the real-time(R) packets,randomized distributed space-time coding(R-DSTC)was used to enhance the reliability of transmission.Simulation results show that NSTCMAC protocol can meet different QoS requirements better,and solve the problem of relays’ low efficiency more effectively,when compared with legacy DCF、COOPMAC and CD-MAC protocol.…”
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Measurement and prediction of the development level of China’s digital economy by Shuangyang Lai, Haoming Chen, Yuexu Zhao

“…Thirdly, this paper establishes Grey-Markov model combining grey system and Markov chain, further uses this model to predict the development level of digital economy. …”
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Computational Procedures for a Class of GI/D/k Systems in Discrete Time by Md. Mostafizur Rahman, Attahiru Sule Alfa

“…Then the queue length is set up as a quasi-birth-death (QBD) type Markov chain. It is shown that this transformed GI/D/1 system has special structures which make the computation of the matrix R simple and efficient, thereby reducing the number of multiplications in each iteration significantly. …”
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Prophet: A Context-Aware Location Privacy-Preserving Scheme in Location Sharing Service by Jiaxing Qu, Guoyin Zhang, Zhou Fang

“…First, we define fingerprint identification based on Markov chain and state classification to describe the users’ behavior patterns. …”
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A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk by Lewei Duan, Duncan C. Thomas

“…The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. …”
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Bayesian Estimation and Prediction for Flexible Weibull Model under Type-II Censoring Scheme by Sanjay Kumar Singh, Umesh Singh, Vikas Kumar Sharma

“…Since the predictive posteriors are not in the closed form, we proposed to use the Monte Carlo Markov chain (MCMC) methods to approximate the posteriors of interest. …”
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Estimation of the coefficients of variation for inverse power Lomax distribution by Samah M. Ahmed, Abdelfattah Mustafa

“…Additionally, it is recommended to use the Markov Chain Monte Carlo (MCMC) method to calculate the Bayes estimate and generate posterior distributions. …”
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Performance Analysis for Priority-Based Broadcast in Vehicular Networks by Rinara Woo, Jung-Hoon Song, Dong Seog Han

“…Firstly, an analytical Markov chain model for vehicle-to-vehicle (V2V) ad hoc communication networks is proposed for broadcasting messages with priority based on the IEEE 802.11p wireless access for vehicular environments (WAVE) standard. …”
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The SEIRS-NIMFA epidemiological model for malware propagation analysis in IoT networks by Laura Quiroga-Sánchez, Germán A. Montoya, Carlos Lozano-Garzon

“…Moreover, to address the Markov chain approach’s high temporal and spatial complexity, we use the n-intertwined mean-field approximation method. …”
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A Mixed Prediction Model of Ground Subsidence for Civil Infrastructures on Soft Ground by Kiyoshi Kobayashi, Kiyoyuki Kaito

“…Concretely speaking, in order to estimate the updating models, Markov Chain Monte Calro method, which is the frontier technique in Bayesian statistics, is applied. …”
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Markov Switching Model Analysis of Implied Volatility for Market Indexes with Applications to S&P 500 and DAX by Luca Di Persio, Samuele Vettori

“…In particular the volatility parameter is treated as an unobserved state variable whose value in time is given as the outcome of an unobserved, discrete-time and discrete-state, stochastic process represented by a suitable Markov chain. We will take into account two different approaches for inference on Markov switching models, namely, the classical approach based on the maximum likelihood techniques and the Bayesian inference method realized through a Gibbs sampling procedure. …”
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Modeling Campaign Optimization Strategies in Political Elections under Uncertainty by Christopher, Senfuka, Paul, Kizito Mubiru, Maureen, N. Ssempijja

“…In most political campaigns,the overall goal of every candidate is to maximize the number of voters during the election exercise.In such an effort,cost effective methods in choosing the optimal campaign strategy areparamount.In this paper, a mathematical model is proposed that optimize campaign strategies of a political candidate.Considering uncertainty in voter support and cost implications in holding political rallies,we formulate a finite state markov decision process model where states of a markov chain represent possible states of support among voters.Using daily equal intervals,thecandidates‟s decision of whether or not to campaign and hold a political rally at a given location were made using discrete time Markov chains and dynamic programming over a finite period planning horizon.Empirical data was collected from two locations on a daily basis during the campaign exercise.The data collected was analyzed and tested to establish the optimal campaign strategy and costs at the respective locations.Results from the study indicated the existence of an optimal state-dependent campaign strategy and costs at the respective political rally locations.…”
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Markov-bridge generation of transition paths and its application to cell-fate choice by Guillaume Le Treut, Sarah Ancheta, Greg Huber, Henri Orland, David Yllanes

“…We present a method to sample Markov-chain trajectories constrained to both the initial and final conditions, which we term Markov bridges. …”
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Modified Chen distribution: Properties, estimation, and applications in reliability analysis by M. G. M. Ghazal

“…Bayesian estimates of the model parameters, along with the survival and hazard functions and their corresponding credible intervals, were derived via the Markov chain Monte Carlo method under balanced squared error loss, balanced linear-exponential loss, and balanced general entropy loss. …”
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On the Effect of Estimation Error for the Risk-Adjusted Charts by Sajid Ali, Naila Altaf, Ismail Shah, Lichen Wang, Syed Muhammad Muslim Raza

“…To compute the average run length (ARL), Markov Chain Monte Carlo simulations are conducted. Furthermore, a bootstrap method is also used to compute the ARL assuming different Phase-I data sets to minimize the effect of estimation error on risk-adjusted control charts. …”
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A two-layer network model of the evolution of public risk perception of emerging technologies by Xiaqun Liu, Xiaoyue Qiu, Yaming Zhuang

“…The evolutionary threshold of public risk perception is analysed using the microscopic Markov chain approach. The influence of public composition and the spread of risk events on the evolution of risk perception is further verified through a simulation. …”
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