Optimal Control for Networked Control Systems with Markovian Packet Losses by Xiao Han, Zhijian Ji, Qingyuan Qi

“…Moreover, the packet loss channels are described with two-state Markov chains. Since the precise state information cannot be obtained, thus an optimal recursive estimator is designed. …”
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Interes konsumenta a interes banku w umowach o kredyt na zakup samochodu by Ryszard Jurkowski

“…Analizy porównawczej dokonano na podstawie dokumentów i odpowiedzi uzyskanych w wyniku bezpośrednich lub elektronicznych kontaktów z bankami, które oferowały konsumentom kredytu na zakup samochodu w okresie marzec – kwiecień 2010 r. Bankom przedstawiono zapytanie potencjalnego klienta o udzielenie kredytu na zakup samochodu, o charakterystyce przedstawionej w artykule.…”
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LINEAR FILTERING OF OUTPUT DATA OF A SINGLE-POSITION SECURITY SYSTEM by B. A. Zaikin

“…A geometric construction of a single-position security system, its mathematical description and formulas of Markov sequence that describes the motion of an object under observation are given. …”
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Dynamic service migration strategy based on MDP model with multiple parameter in vehicular edge network by Hui GUO, Lanlan RUI, Zhipeng GAO

“…To handle with the service interruption caused by vehicles’ mobility and limited service coverage of edge servers,a dynamic service migration algorithm based on multi-parameters Markov decision process (MDP) model was put forward for vehicular edge network,which was called as dynamic service migration algorithm based on multiple parameter (DSMMP).Combining delay,bandwidth,server capacity with vehicle motion information,DSMMP constructed a multi-parameters MDP revenue function to remedy the deficiency of distance-based schemes.By using vehicle motion and delay constraints,a candidate server set with several candidate servers was defined,and migration decision through long-term Bellman revenue values was made.In order to improve the dynamic adaptability of the proposed algorithm,the weight values were calculated and updated by leveraging historical information.Simulation results show that our strategy has a good performance in terms of delay,packet loss ratio and service migration times.…”
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Within‐chain parallelization—Giving Stan Jet Fuel for population modeling in pharmacometrics by Casey Davis, Pavan Vaddady

“…To perform a Bayesian data analysis, most models in pharmacometrics require Markov Chain Monte Carlo (MCMC) methods to sample from the posterior distribution. …”
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Interes konsumenta a interes banku w umowach o kredyt na zakup samochodu by Ryszard Jurkowski

“…Analizy porównawczej dokonano na podstawie dokumentów i odpowiedzi uzyskanych w wyniku bezpośrednich lub elektronicznych kontaktów z bankami, które oferowały konsumentom kredytu na zakup samochodu w okresie marzec – kwiecień 2010 r. Bankom przedstawiono zapytanie potencjalnego klienta o udzielenie kredytu na zakup samochodu, o charakterystyce przedstawionej w artykule.…”
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Joint quadrature modulation and network coding for cooperative Hybrid-ARQ by Xiao-ye SHI, Jian-hua GE, Jing LI, De-feng REN

“…In order to improve the transmission efficiency of quadrature modulated cooperative diversity system,the joint network coding and quadrature modulated scheme for coo ve hybrid automatic repeat request (NC-QM-HARQ)was proposed.By introducing network coding in the retransmission,this scheme could retransmit more information at the same time,thus the retransmission time was saved,resulting in the improvement of the throughput.Furthermore,based on the system's Markov state transition model,the fra error rate (FER)and delay performance in the modulation of M-ary pulse amplitude modulation (PAM)were investigated,therefore the closed approximate solution of the throughput was acquired.Simulation results show that,the proposed s outperforms the traditional quadrature modulated coop-erative diversity system HARQ scheme by a throughput gain of approximate 8% in the following scenes:2PAM modula-tion at 5dB SNR,4PAM at 10dB and 8PAM at 15dB.…”
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On a Stochastic Approach to Extensions of the Susceptible-Infected-Susceptible (SIS) Model Applied to Malaria by Abdoul Karim Drabo, Frédéric Bere, S. P. Clovis Nitiema

“…We first calculated the basic reproduction number R0 of the models ShIhRhSh‐SvIv and ShLhIhRhSh‐SvLvIv in order to show that the malaria-free equilibrium is asymptotically stable; then, we used a finite Markov chain model to describe the interactions between the different compartments of the model SeLeIeReSe‐SaLaIaRaSa‐SvIv. …”
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Estimations in a Constant-Stress Partially Accelerated Life Test for Generalized Rayleigh Distribution under Type-II Hybrid Censoring Scheme by Abdalla Rabie, Eslam Hussam, Abdisalam Hassan Muse, Ramy Abdelhamid Aldallal, Amirah Saeed Alharthi, Hassan M. Aljohani

“…Bayesian and E-Bayesian estimates are obtained using Markov chain Monte Carlo (MCMC) methods. To prove the applicability and the importance of the subject, a test for real data will be provided. …”
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Research on deep reinforcement learning based intelligent shop scheduling method by Zihui LUO, Chengling JIANG, Liang LIU, Xiaolong ZHENG, Huadong MA

“…The unprecedented prosperity of the industrial internet of things (IIoT) has opened up a new path for the traditional industrial manufacturing model.Intelligent shop scheduling is one of the key technologies to achieve the overall control and flexible production of the whole production process.It requires an effective plan with a minimum makespan to allocate multiple processes and multiple machines for production scheduling.Firstly, the shop scheduling problem was defined as a Markov decision process (MDP), and a shop scheduling model based on the pointer network was established.Secondly, the job scheduling process was regarded as a mapping from one sequence to another, and a new shop scheduling algorithm based on deep reinforcement learning (DRL) was proposed.By analyzing the convergence of the model under different parameter settings, the optimal parameters were determined.Experimental results on different scales of public data sets and actual production data sets show that the proposed DRL algorithm can obtain better performances.…”
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Multi-data fusionaided indoor localization based on continuous action space deep reinforcement learning by Xuechen CHEN, Jiaxuan YI, Aixiang WANG, Xiaoheng DENG

“…Significant attention has been paid to indoor localization using smartphones in both research and industry.However, the accuracy and robustness of localization remain challenging issues, particularly in complex indoor environments.In light of the prevalent incorporation of pedestrian dead reckoning (PDR) devices in contemporary smartphones, an advanced indoor localization fusion method, anchored in the twin delayed deep deterministic policy gradient (TD3) framework, was proposed.In this approach, a seamless integration of Wi-Fi information and PDR data was achieved.The localization process of PDR was modeled as a Markov process, and a comprehensive continuous action space was introduced for the agent.To evaluate the performance of the proposed method, experiments were conducted and this approach was compared with three state-of-the-art deep Q network (DQN) based indoor localization methods.The experimental results demonstrate that the proposed method significantly reduces localization errors and enhances overall localization accuracy.…”
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Probabilistic analysis of getting into in restricted area by unmanned aerial vehical by A. A. Lobaty, Y. F. Yatsyna, V. Y. Stepanov, A. Y. Bumai

“…The problem is solved by applying the theory of Markov processes of random structure with absorption of realizations at the boundary of a given area. …”
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Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models by Nachatchapong Kaewsompong, Paravee Maneejuk, Woraphon Yamaka

“…As there are many parameters to be estimated, we consider the Bayesian Markov chain Monte Carlo approach to estimate the parameter interests in the model. …”
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A Novel BBO Algorithm Based on Local Search and Nonuniform Variation for Iris Classification by Lisheng Wei, Ning Wang, Huacai Lu

“…On this base, the convergence condition of NBBO was proposed by using the Markov chain strategy. Finally, simulation results were given to demonstrate the effectiveness and efficiency of the proposed iris classification method.…”
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Some Remarks on Diffusion Distances by Maxim J. Goldberg, Seonja Kim

“…In the second part of the paper, we give two proofs that an extension of mean first passage time to mean first passage cost satisfies the triangle inequality; we do not assume that the underlying Markov matrix is diagonalizable. We conclude by exhibiting an interesting connection between the (normalized) mean first passage time and the discretized solution of a certain Dirichlet-Poisson problem and verify our result numerically for the simple case of the unit circle.…”
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Out-of-Sample Predictability of the Equity Risk Premium by Daniel de Almeida, Ana-Maria Fuertes, Luiz Koodi Hotta

“…A comprehensive out-of-sample forecast evaluation exercise based on statistical and economic loss functions demonstrates the superiority of the proposed approach versus combined forecasts from linear models or Markov switching models and forecasts from machine learning methods such as random forests and gradient boosting. …”
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Dirichlet Forms Constructed from Annihilation Operators on Bernoulli Functionals by Caishi Wang, Beiping Wang

“…Finally, we consider an interesting semigroup of operators associated with w on L2-space of Bernoulli functionals, which we call the w-Ornstein-Uhlenbeck semigroup, and, by using the Dirichlet form, Ew we show that the w-Ornstein-Uhlenbeck semigroup is a Markov semigroup.…”
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Routing algorithm for railway monitoring linear WSN based on improved PSO by Cuiran LI, Xuejie WANG, Jianli XIE, Anqi LYU

“…To solve the problems of short network lifetime and large data transmission delay, caused by unbalanced node energy consumption of linear wireless sensor network in railway monitoring scenario, a routing algorithm based on particle swarm optimization theory and breadth first search was proposed.The fitness function was constructed based on the relative energy consumption, spacing and load of candidate cluster heads.The local search ability of particle swarm algorithm was enhanced by adjusting the inertia weight coefficient to set up the cluster head optimal set.Meanwhile, a path cost function driven by energy consumption and delay was built up, and the optimal main path from the source node to the sink node was obtained by breadth first search.Lastly, a Q-learning alternative path updating and route maintenance mechanism based on discrete Markov decision process (MDP) was designed.Simulation results show that the proposed algorithm can balance the node energy consumption effectively, and has also advantages in prolonging the network lifetime and reducing the data transmission delay.…”
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A Polling-Based Dynamic Order-Picking System considering Priority Orders by Wenxue Ran, Sen Liu, Zhe Zhang

“…A mathematical model is established for such a system by applying polling theory, a probability generating function, and an embedded Markov chain. Numerical analysis shows that this priority polling-based picking system can improve the picking efficiency and is well suited to practical operations.…”
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Bayesian and non-bayesian analysis for stress-strength model based on progressively first failure censoring with applications. by Salem A Alyami, Amal S Hassan, Ibrahim Elbatal, Olayan Albalawi, Mohammed Elgarhy, Ahmed R El-Saeed

“…It is suggested that Markov chain Monte Carlo techniques be used for Bayesian estimation in order to achieve Bayes estimators and the associated credible intervals. …”
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