Application of Intelligent Signal Reflection in the Communication Model of an Electronic Controller by Lan Lan

“…Meanwhile, this paper proposes a fast block-sparse Bayesian learning algorithm. It combines the GAMP algorithm with machine learning, so it can achieve similar performance with much lower computational complexity than the traditional block sparse Bayesian learning algorithm. …”
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Prediction from Transmuted Rayleigh Distribution in the Presence of Outliers by Tahani Ahmad Aloafi

“…Numerical computations are obtained to illustrate the effect of outliers on the Bayesian predictive intervals.…”
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Robust Prediction of Healthcare Inflation Rate With Statistical and AI Methods in Iran by Mohammad Javad Shaibani, Ali Akbar Fazaeli

“…In the next process, by doubling the forecasting window, it is observed that artificial neural network (ANN) (i.e., Bayesian NARANN) strictly outperformed other models. …”
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Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with Applications by Hanan Haj Ahmad

“…Maximum likelihood and Bayesian estimation methods are considered for that purpose. …”
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An Analytical Approach Differentiates Between Individual and Collective Cancer Invasion by Elad Katz, Wim Verleyen, Colin G. Blackmore, Michael Edward, V. Anne Smith, David J. Harrison

“…The Bayesian network separated individual and collective invading cell groups based on the morphological measurements, with the level of cell-cell contact the most discriminating morphological feature. …”
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Population genetic structure of Phaedranassa cinerea Ravenna (Amaryllidaceae) and conservation implications by María Belén Buenaño, Carmen Ulloa Ulloa, Javier Francisco-Ortega, Alan W. Meerow, Nora H. Oleas

“…Results Using 13 microsatellites and a Bayesian approach, we analyzed the genetic differentiation of P. cinerea and possible diversification scenarios. …”
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On Optimal Progressive Censoring Schemes from Models with U-Shaped Hazard Rate: A Comparison between Conventional and Fuzzy Priors by Navid Feroze, Muhammad Noor-ul-Amin, Maryam Sadiq, Md. Moyazzem Hossain

“…This paper explores the optimal censoring schemes from models with U-shaped hazard rates (USHRs) using Bayesian methods. Topp-Leone (TL) distribution has been considered as a special case. …”
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Friction Characteristics of Post-Tensioned Tendons of Full-Scale Structures Based on Site Tests by Haoyun Yuan, Yuan Li, Bin Zhou, Shuanhai He, Peizhi Wang

“…Field test results showed that Bayesian quantile regression method was more effective and significant in the estimation of the friction coefficient.…”
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A PMBGA to Optimize the Selection of Rules for Job Shop Scheduling Based on the Giffler-Thompson Algorithm by Rui Zhang, Cheng Wu

“…Then, the new generation of individuals is produced by sampling the established Bayesian network. Finally, some elitist individuals are further improved by a special local search module based on parameter perturbation. …”
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Geospatial and econometric approaches or older driver safety: Analysis of crash injury severity of regional highways. by Daiquan Xiao, Dajie Zuo, Xuecai Xu, Quan Yuan

“…Results revealed that DBSCAN provides a solid option for hotspot identification of injury severity and Bayesian spatial binary probit model addresses the factor determinants spatially. …”
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Intelligent Method for Identifying Driving Risk Based on V2V Multisource Big Data by Jinshuan Peng, Yiming Shao

“…Characterization parameters for identification were screened and used to determine threshold values and an appropriate time window for identification. A neural network-Bayesian filter identification model was established and data samples were selected to identify risky driving behavior and evaluate the identification efficiency of the model. …”
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A Mixed Prediction Model of Ground Subsidence for Civil Infrastructures on Soft Ground by Kiyoshi Kobayashi, Kiyoyuki Kaito

“…The mixed model can be updated by the Bayesian methods based upon the newly obtained monitoring data. …”
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A stochastic artificial neural network model for investigating street vendor behavior in a night market by Pao-Kuan Wu, Tsung-Chih Hsiao, Ming Xiao

“…This article offers a hybrid computational approach that combines an artificial neural network with Bayesian probability to improve on the conventional artificial neural network model. …”
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An optimized deep-forest algorithm using a modified differential evolution optimization algorithm: A case of host-pathogen protein-protein interaction prediction by Jerry Emmanuel, Itunuoluwa Isewon, Jelili Oyelade

“…However, deep forest-based models have limitations such as manual hyperparameter optimization and time and memory usage inefficiencies. Bayesian optimization is a widely used model-based hyperparameter optimization method. …”
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A novel framework for increasing research transparency: Exploring the connection between diversity and innovation. by Timothy R Wojan, Dayton M Lambert

“…In addition to increasing statistical power by using information from the full sample, Bayesian methods directly estimate a probability distribution for the magnitude of an effect, allowing much richer inference. …”
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Data-driven automated job shop scheduling optimization considering AGV obstacle avoidance by Qi Tang, Huan Wang

“…Meanwhile, a time window is established to control the risk of AGV delay, and a data-driven Bayesian network is constructed to optimize the two-layer scheduling model of automated job shop and AGV. …”
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Detection of Emerging Faults on Industrial Gas Turbines Using Extended Gaussian Mixture Models by Yu Zhang, Chris Bingham, Miguel Martínez-García, Darren Cox

“…An advantage of the variational Bayesian method over traditional predefined thresholds is the extraction of steady-state data during both full- and part-load cases, and a primary advantage of the GMM with an outlier component is its applicability for novelty detection when there is a lack of prior knowledge of fault patterns. …”
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New probabilistic methods for quantitative climate reconstructions applied to palynological data from Lake Kinneret by T. Netzel, A. Miebach, T. Litt, A. Hense

“…The complex age–sediment–depth and proxy–climate relationships must be described in an appropriate way. Bayesian hierarchical models are a promising method for describing such structures.…”
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Automatic Emergence Detection in Complex Systems by Eugene Santos, Yan Zhao

“…We evaluate our detection performance against a baseline approach (Bayesian Network ensemble) on synthetic testbeds from UCI datasets. …”
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Degradation Data-Driven Remaining Useful Life Estimation in the Absence of Prior Degradation Knowledge by Yong Yu, Changhua Hu, Xiaosheng Si, Jianxun Zhang

“…Residual life distributions and posterior distributions are first calculated through the Bayesian updating method based on random initial a priori distributions. …”
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