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A Blended Graph-MCMC Framework for Carbon Emission Reduction in Oil & Gas Supply Chain
Amidst growing global concerns about climate change and heightened environmental awareness, this scholarly paper introduces an innovative approach to...
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Application of a Randomized-Finite Set Statistics Technique (R-FISST) to Space Situational Awareness
This paper presents a novel approach to kee** the Random Finite Set (RFS) based Bayesian recursions tractable. We propose a randomized scheme using...
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Bayesian Model Updating in Time Domain by an Iterated Model Reduction Technique
The present study deals with time domain structural model parameters identification. Specifically, an iterative model reduction algorithm is proposed...
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Bayesian damage identification based on autoregressive model and MH-PSO hybrid MCMC sampling method
Bayesian damage identification method, due to its ability to consider the uncertainties, has attracted much attention from researchers. However,...
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Analysis of Agricultural Commodities Prices Using BART: A Machine Learning Technique
The price analysis of agricultural commodities has both practical and theoretical aspect. In stark contrast to financial markets, this study purposes...
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Identifying Topic Modeling Technique in Evaluating Textual Datasets
One of the most popular methods of topic modeling is Latent Dirichlet Allocation (LDA). To date, philanthropic corporate social responsibility (PCSR)...
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An MCMC based Bayesian inference approach to parameter estimation of distributed lag models for forecasting used product returns for remanufacturing
Forecasting the quantity and timing of used product returns is one of the major challenges faced by remanufacturers. Distributed lag model has been...
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MCMC-Based Probabilistic Damage Characterization for Plate Structures Using Responses at Vibration Nodes
Structural Health Monitoring (SHM) has brought various benefits into the industry, such as in economic, life-safety and lightweight design aspects....
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Mining User Interest Using Bayesian-PMF and Markov Chain Monte Carlo for Personalised Recommendation Systems
It is easy and beneficial to use low-rank matrix approximation techniques in collaborative filtering systems. Model of this kind is often fit by...
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Bayesian inference of airfoil icing condition from simulated ice shapes
Motivated by the difficulty of accurately determining the inflow parameters in icing wind tunnels and flight tests, the Markov Chain Monte Carlo...
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Estimation of Inlet Conditions of Fluid Flow in a Thick Pipe Using Inverse Technique
A conjugate heat transfer problem of steady laminar flow in a circular pipe with a thick wall is considered for estimating inlet conditions of fluid...
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Hybrid Bayesian and modified grey PROMETHEE-AL model-based trust estimation technique for thwarting malicious and selfish nodes in MANETs
Cooperation among mobile nodes during the routing process is indispensable for attaining reliable data delivery between the source and destination...
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Gibbs Sampling-based Sparse Estimation Method over Underwater Acoustic Channels
The estimation of sparse underwater acoustic (UWA) channels can be regarded as an inference problem involving hidden variables within the Bayesian...
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Bayesian Inference of Hidden Markov Models Using Dirichlet Mixtures
In this chapter, we propose an efficient unsupervised learning approach following a Bayesian framework for Hidden Markov Model (HMM) learning. We...
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Stochastic Aeroelastic Modeling Using Bayesian Inference
This study focuses on stochastic modelling of 2D aeroelastic model to quantify the uncertainties in the parameters of aeroelastic models,...
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Probabilistic estimation of directional wave spectrum using onboard measurement data
Ocean wave spectrum is the key to the response estimation of seagoing vessel whose structural integrity is of utmost importance. Efforts have been...
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How Does Energy Consumption Matter for Economic Growth? A Bayesian Data Analysis
Energy is traditionally regarded to significantly contribute to most economic activities. Countries select the type of energy most appropriate for...
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Subset simulation with adaptable intermediate failure probability for robust reliability analysis: an unsupervised learning-based approach
Subset simulation ( SS ) was known for its computational efficiency in estimating small failure probabilities as well as reducing emulation demands....
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A Bayesian Approach to Lamb-Wave Dispersion Curve Material Identification in Composite Plates
Guided waves are gaining increased interest in SHM, thanks to some distinct advantages. For guided-wave-based localisation strategies, information on...
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Bayesian Structured-Sparse Modeling Using a Bernoulli–Laplacian Prior
Recently, sparse signal and image recovery have shown significant promise in different biomedical fields. In this paper, we introduce a novel method...
