Adaptive Localization in Wireless Sensor Network through Bayesian Compressive Sensing by Zuoxin Xiahou, Xiaotong Zhang

“…The estimation of the localization of targets in wireless sensor network is addressed within the Bayesian compressive sensing (BCS) framework. …”
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Adaptive capacity to climate change in the wine industry: A Bayesian Network approach by Eva Merloni, Luca Camanzi, Luca Mulazzani, Giulio Malorgio

“…Keywords: Climate change, Adaptive capacity, Wine sector, Bayesian Network…”
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Bayesian network structure learning algorithm based on hybrid binary salp swarm-differential evolution algorithm by Bin LIU, Ruixing FAN, Haoran LIU, Liyue ZHANG, Haiyu WANG, Chunlan ZHANG

Subjects: “…Bayesian network structure learning…”
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Enhancing autonomous systems with bayesian neural networks: a probabilistic framework for navigation and decision-making by Ngartera Lebede, Saralees Nadarajah

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Bayesian Optimized ANFIS Network Using Grid Partition and Feature Spectrum for Urban Light Pollution Assessment by Nuoqi Wang, Cheng Wang, Zhihong Zhao, Peiyu Wu, Wenqian Xu, Bang Qin, Dong Wang, Rongjun Zhang, Qi Yao

“…Building on this, we have developed an Adaptive Neuro-fuzzy Inference System (ANFIS) structure utilizing global Bayesian optimization and grid partitioning (GP), which integrates the advantages of fuzzy logic in handling data uncertainty with the self-learning capabilities of artificial neural networks. …”
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An adaptive defense mechanism to prevent advanced persistent threats by Yi-xi Xie, Li-xin Ji, Ling-shu Li, Zehua Guo, Thar Baker

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An automatic adaptive method to combine summary statistics in approximate Bayesian computation. by Jonathan U Harrison, Ruth E Baker

“…To infer the parameters of mechanistic models with intractable likelihoods, techniques such as approximate Bayesian computation (ABC) are increasingly being adopted. …”
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Control Theory and Bayesian Networks for Black Spots Study by Leonardo Flores, Jorge Vargas, Alan Ayala, Jeremy Ramos, Edwin Salas

“…To predict whether a traffic accident occurs at a black spot, a Bayesian network is employed, which also indicates the reliability of the accident classification result. …”
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MOBILE LEARNING: CONTEXT ADAPTATION AND SCENARIO APPROACH by Vladimir V. Kureichik, Sergey I. Rodzin, Lada S. Rodzina

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Envisioning the future of wildlife in a changing climate: Collaborative learning for adaptation planning by Olivia E. Ledee, William H. Karasov, Karl J. Martin, Michael W. Meyer, Christine A. Ribic, Timothy R. Van Deelen

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Bayesian Adaptive Extended Kalman-Based Orbit Determination for Optical Observation Satellites by Yang Guo, Qinghao Pang, Xianlong Yin, Xueshu Shi, Zhengxu Zhao, Jian Sun, Jinsheng Wang

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Research of trust evaluation model based on dynamic Bayesian network by Hong-quan LIANG, Wei WU

“…Trust evaluation model needs to be developed for trusted network.Based on interpersonal trust model in sociology,the trusted relationship between network nodes was researched,and a trust evaluation model based on dynamic bayesian network associating with time factor as proposed.The impact of authentication and network interaction behavior was fully considered,and historical interaction window,timelin factor and penalty factor were introduced.Also,the polymerization method of the direct trust de ee and indirect trust degree was given,and the dynamic adaptive ability of the model was improved as well as the calculation of the sensitivity and accuracy.Furthermore,the threaten of abnormal entity was effectively suppressed.Experimental results show that this model computes the trust degree more sensitively and effecti ly as well as better dynamic adaptivity compared with the traditional bayesian network model.…”
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Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers by Gonzalo A. Ruz, Pamela Araya-Díaz

“…For this, we present adaptations of classical Bayesian networks classifiers to handle continuous attributes; also, we propose an incremental tree construction procedure for tree like Bayesian network classifiers. …”
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Transmuted Generalized Weibull Lindley (TGWL) distribution: Bayesian inference and Bayesian neural network approaches for lifetime data modeling by Pius Marthin, Gadde Srinivasa Rao

“…Through extensive simulation, we demonstrate that classical techniques such as Maximum Likelihood Estimation (MLE) struggle to address uncertainty in model parameters in complex lifetime models such as TGWL, while Bayesian Inference and Bayesian Neural Network (BNN) achieve outstanding performance both in terms of accuracy and robustness. …”
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Bayesian Optimized GridDehazeNet for Adaptive Haze Removal in Real-World Applications by Sungkwan Youm

“…While models like GridDehazeNet enhance dehazing performance, our research emphasizes that selecting appropriate image data and application methods is even more crucial. We propose an adaptive haze removal system that integrates Bayesian Optimization with GridDehazeNet to automatically find the optimal network width and height for specific environments. …”
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Integrating Bayesian classification and ANN for lithofacies classification using well and seismic data: Bahregansar case study by Hessam Mansouri Siahgoli, Mohammad Ali Riahi, Majid Nabi-Bidhendi, Seyedmohsen Seyedali

Subjects: “…Bayesian classification…”
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Performance and Adaptability Testing of Machine Learning Models for Power Transmission Network Fault Diagnosis With Renewable Energy Sources Integration by Rachna Vaish, Umakant Dhar Dwivedi

“…The ongoing integration of renewable energy sources (RES) into the existing transmission networks alters the system topology, potentially resulting in significant changes in fault signatures depending on the size of the newly added RES. …”
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An Adaptive Robust Event-Triggered Variational Bayesian Filtering Method with Heavy-Tailed Noise by Di Deng, Peng Yi, Junlin Xiong

“…Event-triggered state estimation has attracted significant attention due to the advantage of efficiently utilizing communication resources in wireless sensor networks. In this paper, an adaptive robust event-triggered variational Bayesian filtering method is designed for heavy-tailed noise with inaccurate nominal covariance matrices. …”
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Edge-Fog Computing-Based Blockchain for Networked Microgrid Frequency Support by Ying-Yi Hong, Francisco I. Alano, Yih-der Lee, Chia-Yu Han

“…The parameters and hyperparameters of the LSTM-MFPC are optimized using the Bayesian Adaptive Direct Search (BADS) algorithm. The root mean square error (RMSE) of the current obtained using the traditional model predictive control (MPC) and the proposed LSTM-MFPC applied to the inverter are 0.1970 and 0.1432, respectively. …”
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A Bayesian approach to discrete multiple outcome network meta-analysis. by Rebecca Graziani, Sergio Venturini

“…In this paper we suggest a new Bayesian approach to network meta-analysis for the case of discrete multiple outcomes. …”
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