Accident Data-Driven Consequence Analysis in Maritime Industries by Jiahui Shi, Zhengjiang Liu

“…Thirdly, a TAN (Tree Augmented Network)-based BN (Bayesian network) model is developed. Fourthly, a model validation process, including a comparative analysis, Kappa test, and scenario analysis are performed. …”
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Combined AGADESN with DBSCAN Algorithm for Cluster Target Motion Intention Recognition by Xirui Xue, Shucai Huang, Daozhi Wei

“…This is a challenge to the classical Bayesian inference based intention recognition algorithms because they rely heavily on a priori knowledge. …”
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Modified Chen distribution: Properties, estimation, and applications in reliability analysis by M. G. M. Ghazal

“…Model parameters, along with survival and hazard functions, were estimated by utilizing maximum likelihood estimators and two types of bootstrap confidence intervals. 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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Abnormal Event Detection in Wireless Sensor Networks Based on Multiattribute Correlation by Mengdi Wang, Anrong Xue, Huanhuan Xia

“…A dependency model of observed attributes is constructed based on Bayesian network. In this model, the dependency structure of observed attributes is obtained by structure learning, and the conditional probability table of each node is calculated by parameter learning. …”
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Analysis of Freeway Secondary Crashes in Different Traffic Flow States by Three-Phase Traffic Theory by Bo Yang, Yao Wu, Weihua Zhang

“…The traffic flow states are categorised by three-phase traffic theory. The Bayesian conditional logit model has been established to analyse the statistical relationship between the secondary crash probability and various traffic flow states. …”
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Optimal Joint Defense and Monitoring for Networks Security under Uncertainty: A POMDP-Based Approach by Armita Kazeminajafabadi, Mahdi Imani

“…The increasing interconnectivity in our infrastructure poses a significant security challenge, with external threats having the potential to penetrate and propagate throughout the network. Bayesian attack graphs have proven to be effective in capturing the propagation of attacks in complex interconnected networks. …”
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Determination of the best time series model for forecasting annual rainfall of selected stations of Western Azerbaijan province by Somayeh Soltani gerdfaramarzi, Aref Saberi, Morteza Gheisouri

“…With regard to the evaluation criterion such as T, P-VALUE < 0.05 and Bayesian Information Creterion (BIC), ARIMA (1,0,0), ARIMA (0,1,1) and ARIMA (0,1,1) models was determined as a suitable model for predicting annual rainfall in the three selected stations at Uromiya, Makoo and Mahabad. …”
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Optimizing Poisson-Lindley Parameter Estimation: LQM and Reliability Analysis Applied to Guinea Pig Survival Data by Sameera Othman

“…Based on mean square error criteria(MSE), Akaike information criterion (AIC), and Bayesian information criterion (BIC), Linear Quantile-Moment is the most efficient estimator among these techniques. …”
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Equilibrium Signal and Purchase Decision in China’s IPO Net Roadshow: A Dynamic Game Approach by Yi Zhao, Dong Li

“…In conclusion, there exist unique separating equilibrium and pooling equilibrium as a perfect Bayesian Nash equilibrium, and the existence and uniqueness of their equilibrium domains have been verified by numerical simulation. …”
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Data-based regression models for predicting remifentanil pharmacokinetics by Prathvi Shenoy, Mahadev Rao, Shreesha Chokkadi, Sushma Bhatnagar, Naveen Salins

“…By optimising the hyperparameters with Bayesian methods, the performance of these models is significantly improved, attaining the minimum MSE value. …”
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Institutions, Voids, and Dependencies: Tracing the Designs and Robustness of Urban Water Systems by Aaron Deslatte, Elizabeth A. Koebele, Lauren Bartels, Adam Wiechman, Sara Alonso Vicario, Celeste Coughlin, Desi Rybolt

“…This study develops a Bayesian application of the Robustness of Coupled Infrastructure Systems (CIS) Framework to analyze how the institutional design of a major U.S. urban water system impacts information flow and, ultimately, the goal of resource-delivery robustness. …”
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Preserving information while respecting privacy through an information theoretic framework for synthetic health data generation by Nadir Sella, Florent Guinot, Nikita Lagrange, Laurent-Philippe Albou, Jonathan Desponds, Hervé Isambert

“…Here, we introduce a novel algorithm (MIIC-SDG) for generating synthetic data from electronic records based on a multivariate information framework and Bayesian network theory. We also propose a new metric to quantitatively assess the trade-off between the Quality and Privacy Scores (QPS) of synthetic data generation methods. …”
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Integrating psychological and mental health perspectives in disease management: improving patient well-being by Francesca Grosso

“…Furthermore, integrating a Bayesian interpretation of the human mind into healthcare helps discourage reliance on a singular perspective, ensuring a broader understanding of patient needs and contexts informs medical decisions. …”
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Design and Implementation of Community Pension Service Quality Evaluation System Based on Clustering Algorithm by Weiwei Liu

“…We use text mining technology and emotion analysis to determine the relationship between comment emotion and community elderly care service quality online and build a quality emotion feature library. The naive Bayesian algorithm is used to classify the online evaluation of the service quality of community elderly care services, which verified by experiments and completed the design and development of the community elderly care service quality evaluation system based on the project needs.…”
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Parameter estimation of social forces in pedestrian dynamics models via a probabilistic method by Alessandro Corbetta, Adrian Muntean, Kiamars Vafayi

“…Focusing on a specific crowd dynamics situation, including real lifeexperiments and measurements, our paper targets a twofold aim: (1) wepresent a Bayesian probabilistic method to estimate the value and theuncertainty (in the form of a probability density function) ofparameters in crowd dynamic models from the experimental data; and (2)we introduce a fitness measure for the models to classify acouple of model structures (forces) according to their fitness to theexperimental data, preparing the stage for a more generalmodel-selection and validation strategy inspired by probabilistic dataanalysis. …”
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Analysis of Factors Affecting Road Transport Accidents of Hazardous Materials Based on PG-BN by Zewen Li, Mengmeng Zhang

“…To analyze the factors affecting road accidents involving hazardous materials, the Bayesian network (BN) model was used to fit the accident data. …”
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An advection-diffusion-reaction size-structured fish population dynamics model combined with a statistical parameter estimation procedure: Application to the Indian Ocean skipjack... by Blaise Faugeras, Olivier Maury

“…We thendiscuss the numerical scheme chosen for the integration of thesimulation model.In a second step we address the parameter estimation problem for such a model.With the help of automatic differentiation, we derive the adjoint code which is usedto compute the exact gradient of a Bayesian cost functionmeasuring the distance between the outputs of the model and catch and length frequency data.A sensitivity analysis shows that not all parameters can be estimated from the data.Finally twin experiments in which pertubated parameters are recoveredfrom simulated data are successfully conducted.…”
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Classification and Analysis of College Students’ Skills Using Hybrid AI Models by Huili Tang, Yanhong Wei

“…The process specifically utilizes the Rasch statistical analysis model and an innovative fuzzy Bayesian network. Higher-level reasoning is generated for the automated and personalized learning process in which college students are automatically classified into a certain category based on their skills.…”
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Optimization of Sample Size, Data Points, and Data Augmentation Stride in Vibration Signal Analysis for Deep Learning-Based Fault Diagnosis of Rotating Machines by Fasikaw Kibrete, Dereje Engida Woldemichael, Hailu Shimels Gebremedhen

“…To address this challenge, this paper proposes a new adaptive method based on Bayesian optimization to determine the optimal combination of these input parameters from raw vibration signals and enhance the diagnostic performance of deep learning models. …”
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SPACIER: on-demand polymer design with fully automated all-atom classical molecular dynamics integrated into machine learning pipelines by Shun Nanjo, Arifin, Hayato Maeda, Yoshihiro Hayashi, Kan Hatakeyama-Sato, Ryoji Himeno, Teruaki Hayakawa, Ryo Yoshida

“…We developed SPACIER, an open-source software program that incorporates RadonPy, a Python library for fully automated polymer physical property calculations based on all-atom classical molecular dynamics, into a Bayesian optimization-based polymer design system to overcome these challenges. …”
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