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Markov Chain Monte Carlo Methods
The Markov Chain Monte Carlo (MCMC) methods based on the Bayes theorem are used when an a posteriori distribution does not have a tractable form and...
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A Markov Chain-Based Group Consensus Method with Unknown Parameters
Group consensus (GC) is important for generating a group solution satisfactory or acceptable to most decision-makers in a group. Its convergency...
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Project cost forecasting based on earned value management and Markov chain
The most issue in project management is estimating the required budget for the project. Today, despite all the progress and relative achievement of...
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Markov Chain
Understand the Markov process and the basic concept of Markov.
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Markov interval chain (MIC) for solving a decision problem
One of the main missions of a certain company is to predict its future for reasons of continuity, which reflect the balance of its long term, in...
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Application of Markov chain to share price movement in Nigeria (1985–2019)
The study evaluates the movement of share prices in the Nigerian stock market. Markov chain approach provides a successful analysis and prediction of...
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Dynamic offer creation for airline ancillaries using a Markov chain choice model
Customers have become accustomed to a highly streamlined and personalized experience when shop** online. While tech giants such as Apple, Amazon,...
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Discrete Markov Processes and Numerical Algorithms for Markov Chains
This chapter states the necessary classical results on discrete-time Markov processes and presents some approaches for determining the basic...
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Understanding transitions in professors’ evaluation: the application of Markov chain
Professors’ evaluations are carried out differently throughout individual universities, but it is an important part of a university internal quality...
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Subexponential asymptotics of asymptotically block-Toeplitz and upper block-Hessenberg Markov chains
This paper studies the subexponential asymptotics of the stationary distribution vector of an asymptotically block-Toeplitz and upper...
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Queueing system with control by admission of retrial requests depending on the number of busy servers and state of the underlying process of Markov arrival process of primary requests
A multi-server retrial queuing model is under study. Arrivals occur according to the Markov arrival process ( MAP ). Aiming to increase the probability...
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Joint chance-constrained Markov decision processes
We consider a finite state-action uncertain constrained Markov decision process under discounted and average cost criteria. The running costs are...
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Markov approach for reliability-availability-maintainability analysis of a three unit repairable system
In this article, the use of Markov approach has been made to analyze the reliability, availability and maintainability of a repairable system. The...
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Routing in Reinforcement Learning Markov Chains
With computers beating human players in challenging games like Chess, Go, and StarCraft, Reinforcement Learning has gained much attention recently....
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Stress testing for IInd pillar life-cycle pension funds using hidden Markov model
This paper presents a stress testing technique based on a hidden Markov regime switching model and scenario generations. Firstly, we assume that...
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A new dynamic multi-attribute decision making method based on Markov chain and linear assignment
This paper presents a new Dynamic Multi-Attribute Decision-Making method based on Markovian property, which can predict the performance of each...
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On Nash-solvability of n-person graphical games under Markov and a-priori realizations
We consider finite graphical n -person games with perfect information that have no Nash equilibria in pure stationary strategies. Solving these games...
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Markov Decision Processes of a Two-Tier Supply Chain Inventory System
Our supply chain (SC) model is based on a two-tier queueing-inventory system. This facility delivers packages of Q > 0 fixed-size items from its...
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Supply Chain Risk and Resilience Analytics
This chapter is devoted to the principles and applications of supply chain analytics to resilience analysis and stress testing the supply networks....
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Deep reinforcement learning imbalanced credit risk of SMEs in supply chain finance
It is crucial to predict the credit risk of small and medium-sized enterprises (SMEs) accurately for the success of supply chain finance (SCF)....
