Results 61 to 70 of about 42,084 (260)

Independence Decomposition in Dynamic Bayesian Networks [PDF]

, 2007
Dynamic Bayesian networks are a special type of Bayesian network that explicitly incorporate the dimension of time. They can be distinguished into repetitive and non-repetitive networks. Repetitiveness implies that the set of random variables of the network and their independence relations are the same at each time step.
Flesch, I., Lucas, Peter
openaire   +2 more sources

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Predictive Analytics by Using Bayesian Model Averaging for Large-Scale Internet of Things

International Journal of Distributed Sensor Networks, 2013
Massive events can be produced today because of the rapid development of the Internet of Things (IoT). Complex event processing, which can be used to extract high-level patterns from raw data, has become an essential part of the IoT middleware ...
Xinghui Zhu, Fang Kui, Yongheng Wang
doaj   +1 more source

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

Bayesian Deep Learning for Dynamic Power System State Prediction Considering Renewable Energy Uncertainty

Journal of Modern Power Systems and Clean Energy, 2022
Modern power systems are incorporated with distributed energy sources to be environmental-friendly and cost-effective. However, due to the uncertainties of the system integrated with renewable energy sources, effective strategies need to be adopted to ...
Shiyao Zhang, James J.Q. Yu
doaj   +1 more source

Ultrasmall High‐Entropy Materials: Nanoscale Effects, Synthesis, and Mechanistic Insights

Advanced Functional Materials, EarlyView.
This review article focuses on sub‐10 nm high‐entropy materials that combine nanoscale design with complex compositions for next‐generation applications. ABSTRACT Ultrasmall high‐entropy nanomaterials (USHENMs, <10 nm) merge multicomponent chemistry with size‐dependent effects, forming a distinct class of materials with unprecedented properties.
Yueyue He, Wenbo Wang, Simon Schweidler, Yanjiao Ma, Ben Breitung, Torsten Brezesinski   +5 more
wiley   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

A fuzzy rough copula Bayesian network model for solving complex hospital service quality assessment

Complex & Intelligent Systems, 2023
Healthcare tends to be one of the most complicated sectors, and hospitals exist at the core of healthcare activities. One of the most significant elements in hospitals is service quality level.
He Li, Mohammad Yazdi, Hong-Zhong Huang, Cheng-Geng Huang, Weiwen Peng, Arman Nedjati, Kehinde A. Adesina   +6 more
doaj   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Research of trust evaluation model based on dynamic Bayesian network

Tongxin xuebao, 2013
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
Hong-quan LIANG, Wei WU
doaj   +2 more sources