The paper contains a discussion on mathematical modifying and redesigning DNA with the use of Markov chains. We give a simple mathematical technique for overwriting missing parts of DNA. With a certain probability (without even knowing the function o...
We introduce a bivariate Markov chain counting process with contagion for modelling the clustering arrival of loss claims with delayed settlement for an insurance company. It is a general continuous-time model framework that also has the potential to...
We consider the problem of estimating the measure of subsets in very large networks. A prime tool for this purpose is the Markov Chain Monte Carlo (MCMC) algorithm. This algorithm, while extremely useful in many cases, still often suffers from the dr...
16 February 2023
Poor mental health affects nearly one billion people worldwide and can end in suicide if not treated. Unfortunately, stigma and a lack of mental healthcare providers are barriers to receiving needed care. We developed a Markov chain model to determin...
We consider a Markov chain that can be termed a discrete version of Blackwell’s example from 1958. It is constructed with the aid of a sequence of independent Markov chains with two states. It turns out its stationary distribution
A formulation is presented for the assessment of the CO2 generated by ships in operation and their evolution with time, conditional on the current legislation using Markov chains. Any potential deep repair or retrofitting of the ship propulsion syste...
The optimization of maintenance in healthcare buildings reduces operating costs and contributes towards increasing the sustainability of the healthcare system. This paper proposes a tool to schedule preventive maintenance for healthcare centers using...
Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte C...
This paper proposes a short-term water demand forecasting method based on the use of the Markov chain. This method provides estimates of future demands by calculating probabilities that the future demand value will fall within pre-assigned intervals...
Markov chain perturbation theory is a rapidly developing subfield of the theory of stochastic processes. This review outlines emerging applications of this theory in the analysis of stochastic models of chemical reactions, with a particular focus on...
Abnormal behavioral changes in the regular daily mobility routine of a pregnant dairy cow can be an indicator or early sign to recognize when a calving event is imminent. Image processing technology and statistical approaches can be effectively used...
We present a mortality model where future stochastic changes in population-wide mortality are driven by a finite-state hierarchical Markov chain. A baseline mortality in an initial ‘Alive’ state is calculated as the average logarithm of t...
In this study, urban growth of the Atakum District in Samsun, Turkey, was simulated by Cellular Automata-Markov Chain (CA-MC) and Multi-layer Perceptron-Markov Chain (MLP-MC) hybrid models in a geographical information system (GIS) environment. Histo...
The switching system model of a closed-loop supply chain with Markov jump parameters is established. The system is modeled as a switching system with Markov jump parameters, taking into account the uncertainties of the process and the inventory decay...
This study improves an approach for Markov chain-based photovoltaic-coupled energy storage model in order to serve a more reliable and sustainable power supply system. In this paper, two Markov chain models are proposed: Embedded Markov and Absorbing...
A Markov chain is commonly used in stock market analysis, manpower planning, and in many other areas because of its efficiency in predicting long run behavior. However, the Air Quality Index (AQI) suffers from not using a Markov chain in its forecast...
The expansion of global production networks has raised many important questions about the interdependence among countries and how future changes in the world economy are likely to affect the countries’ positioning in global value chains. We are...
Urban expansion is considered as one of the most important problems in several developing countries. Bangkok Metropolitan Region (BMR) is the urbanized and agglomerated area of Bangkok Metropolis (BM) and its vicinity, which confronts the expansion p...
A practical probabilistic data association filter is proposed for tracking multiple targets in clutter. The number of joint data association events increases combinatorially with the number of measurements and the number of targets, which may become...
In multiple detection target tracking environments, PDA-based algorithms such as multiple detection joint integrated probabilistic data association (MD-JIPDA) utilize the measurement partition method to generate measurement cells. Thus, one-to-many t...
This paper proposes a novel approach that makes use of continuous-time Markov chains and regret functions to find an appropriate compromise in the context of multicriteria decision analysis (MCDA). This method was an innovation in the relationship be...
Markov chain Monte Carlo sampling propagators, including numerical integrators for stochastic dynamics, are central to the calculation of thermodynamic quantities and determination of structure for molecular systems. Efficiency is paramount, and to a...
To address the urgent need to accurately predict the spreading trend of the COVID-19 epidemic, a continuous Markov-chain model was, for the first time, developed in this work to predict the spread of COVID-19 infection. A probability matrix of infect...
Accurate prediction and management of the service life of buildings and structural components are crucial for ensuring durability and economic efficiency. This paper investigates both discrete- and continuous-time Markov chains as probabilistic model...
Traditional oil tank detection methods often use geometric shape information. However, it is difficult to guarantee accurate detection under a variety of disturbance factors, especially various colors, scale differences, and the shadows caused by vie...
In this study, an application of deep learning-based neural computing is proposed for efficient real-time state estimation of the Markov chain underwater maneuvering object. The designed intelligent strategy is exploiting the strength of nonlinear au...
This paper proposes a framework for assessing the financial sustainability of a wine producing company. The probabilistic approach is used to model the expected changes in the financial situation of an enterprise based on the historical trends. The c...
Establishing fast and reversible photon multiple scattering algorithms remains a modeling challenge for optical diagnostics and noise reduction purposes, especially when the scattering happens within the intermediate scattering regime. Previous work...
By means of compressive sampling (CS), a sparse signal can be efficiently recovered from its far fewer samples than that required by the Nyquist–Shannon sampling theorem. However, recovering a speech signal from its CS samples is a challenging...
Structural network pruning is an effective way to reduce network size for deploying deep networks to resource-constrained devices. Existing methods mainly employ knowledge distillation from the last layer of network to guide pruning of the whole netw...
Ribonucleic acid (RNA) secondary structures and branching properties are important for determining functional ramifications in biology. While energy minimization of the Nearest Neighbor Thermodynamic Model (NNTM) is commonly used to identify such pro...
The effectiveness of depth information in saliency detection has been fully proved. However, it is still worth exploring how to utilize the depth information more efficiently. Erroneous depth information may cause detection failure, while non-salient...
This paper proposes a genetic algorithm-based Markov Chain approach that can be used for non-parametric estimation of regression coefficients and their statistical confidence bounds. The proposed approach can generate samples from an unknown probabil...
In order to improve the dynamic optimization of fleet size and standardized management of dockless bike-sharing, this paper focuses on using the Markov stochastic process and linear programming method to solve the problem of bike-sharing fleet size a...
We present a two-country model (North and South) that describes the phenomenon of offshoring and reshoring. The model is a continuous time-controlled Markov chain with binary states. The main trade-off involves production costs and transaction costs...
Researchers have proposed many approaches to identify key classes in software from the perspective of complex networks, such as CONN-TOTAL-W,
Performance analysis and design space exploration of bufferless Networks-on-Chip is done mainly through time-consuming cycle-accurate simulation, due to the chaotic nature of packet deflections, which have thus far prevented the development of an acc...
Respiratory Sinus Arrhythmia (RSA) manifests as cyclic fluctuations in heart rate in synchrony with breathing. Gaining insights into the dynamics of RSA within the cardiac muscle functioning is crucial for comprehending its physiological and clinical...
Discrete, finite-state Markov chains are applied in many different fields. When a system is modeled as a discrete, finite-state Markov chain, the asymptotic properties of the system, such as the steady-state distribution, are often estimated based on...
This study analyzed the spillovers among intra-urban housing submarkets in Beijing, China. Intra-urban spillover imposes a methodological challenge for housing studies from the spatial and temporal perspectives. Unlike the inter-urban spillover, the...
In this study Markov chains process in combination with chi-squared test were applied to hydrological drought dataset of Nestos hydrosystem to highlight the drought transition attitude from one drought state to another. This examined hydrosystem is o...
Due to advancements in CPU and storage technologies, the processing speed of tasks has been increasing. However, there has been a relative slowdown in the data transfer speeds between disks and memory. Consequently, the issue of I/O processing speed...
Agricultural crop yield prediction is vital for ensuring global food security and optimizing resource management amid the increasing challenges posed by climate change and extreme weather variability. This study investigates the use of discrete-time,...
Bias correction methods are routinely used to correct climate model outputs for hydrological and agricultural impact studies. Even though superior bias correction methods can correct the distribution of daily precipitation amounts, as well as the wet...
The evaluation of localized soil-liquefaction potential is based primarily on the individual evaluation of the liquefaction potential in each borehole, followed by calculating the liquefaction-potential index between boreholes through Kriging interpo...
The object under investigation is a controllable linear stochastic differential system affected by some external statistically uncertain piecewise continuous disturbances. They are directly unobservable but assumed to be a continuous-time Markov chai...
This paper presents a real-time handover and link assignment framework for low-Earth-orbit (LEO) satellite networks operating in dense urban canyons. The proposed Markov chain-guided simulated annealing (MCSA) algorithm optimizes user-to-satellite as...
Grey prediction models for time series have been widely applied to demand forecasting because only limited data are required for them to build a time series model without any statistical assumptions. Previous studies have demonstrated that the combin...
This paper presents a stochastic Markov chain model for estimating new entrants into professional orders and their related pension funds. The model considers the interactions between demographic, socio-economic and regulatory variables. The intuition...
The use of individual calving pens in modern farming is widely recognized as a good practice for promoting good animal welfare during parturition. However, determining the optimal time to move a pregnant cow to a calving pen can be a management chall...
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