Results 71 to 80 of about 235,639 (329)
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
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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
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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
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Learning dynamic Bayesian networks [PDF]
, 1998 Bayesian networks are a concise graphical formalism for describing probabilistic models. We have provided a brief tutorial of methods for learning and inference in dynamic Bayesian networks. In many of the interesting models, beyond the simple linear dynamical system or hidden Markov model, the calculations required for inference are intractable.
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Superionic Amorphous Li2ZrCl6 and Li2HfCl6
Advanced Materials, EarlyView.Amorphous Li2HfCl6 and L2ZrCl6 are shown to be promising solid‐state electrolytes with predicted ionic conductivities >20 mS·cm−1. Molecular dynamics simulations with machine‐learning force fields reveal that anion vibrations and flexible MCl6 octahedra soften the Li coordination cage and enhance mobility. Correlation between Li‐ion diffusivity and the
Shukai Yao, De‐en Jiang
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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 +6 more
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Feature Dynamic Bayesian Networks
Proceedings of the 2nd Conference on Artificial General Intelligence (2009), 2009 Feature Markov Decision Processes (PhiMDPs) are well-suited for learning agents in general environments. Nevertheless, unstructured (Phi)MDPs are limited to relatively simple environments. Structured MDPs like Dynamic Bayesian Networks (DBNs) are used for large-scale real-world problems. In this article I extend PhiMDP to PhiDBN.
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Advanced Materials, EarlyView.The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
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Dynamic early warning of rockburst using microseismic multi-parameters based on Bayesian network
Engineering Science and Technology, an International Journal, 2021 Rockburst is a phenomenon where the elastic deformation may be emitted suddenly because of rock fragmentation, ejection, launching, and even earthquake.
Xiang Li, Haoyu Mao, Biao Li, Nuwen Xu
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Magnetic Textiles: A Review of Materials, Fabrication, Properties, and Applications
Advanced Materials Technologies, EarlyView.Magnetic textiles (M‐textiles) are emerging as a programmable materials platform that merges magnetic matter with hierarchical textile structures. This article consolidates magnetic material classes, textile architectures, and fabrication and magnetization strategies, revealing structure–property–function relationships that govern magneto‐mechanical ...
Li Ke +3 more
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