Results 121 to 130 of about 35,631 (308)

Computing non-Newtonian fluid flow with radial basis function networks

, 2005
This paper is concerned with the application of radial basis function networks (RBFNs) for solving non-Newtonian fluid flow problems. Indirect RBFNs, which are based on an integration process, are employed to represent the solution variables; the ...
R. I. Tanner, Mai-Duy, N., N. Mai-Duy, Tanner, R. I.   +3 more
core   +1 more source

Advancing Lithium–Oxygen Batteries: Pioneering Cathode Catalyst Innovation and Artificial Intelligence‐Driven Design Paradigms

Advanced Materials, EarlyView.
This review summarizes the principles and challenges of nonaqueous lithium‐oxygen batteries and recent advances in cathode catalysts, including carbon‐based materials, metals, oxides, sulfides, nitrides, carbides, and redox mediators. It highlights emerging design strategies and artificial intelligence‐driven approaches, emphasizing data‐assisted ...
Yuqing Yao, Chongyang Hao, Karol Viviana Mejia‐Centeno, Malik Dilshad Khan, Shang Wang, Longqiu Li, Yanhong Tian, Andreu Cabot, Qing Sun   +8 more
wiley   +1 more source

Advances in Magnesium‐Based Thermoelectrics: A Critical Review

Advanced Materials, EarlyView.
Magnesium‐based thermoelectric materials have emerged as promising candidates for low‐to‐mid‐temperature energy conversion due to their abundance, low cost, and competitive performance. This review summarizes recent advances in Mg3X2, MgAgSb, and Mg2X systems, covering transport mechanisms, fabrication strategies, stability challenges, and device ...
Li‐Min Zhang, Li Zhang, Nan‐Hai Li, Yan‐Ling Yang, Xiao‐Lei Shi, Zhi‐Gang Chen   +5 more
wiley   +1 more source

Classification Improvement with Integration of Radial Basis Function and Multilayer Perceptron Network Architectures

Mathematics
The radial basis function architecture and the multilayer perceptron architecture are very different approaches to neural networks in theory and practice.
László Kovács
doaj   +1 more source

Kolmogorov-Arnold Networks are Radial Basis Function Networks

CoRR
This short paper is a fast proof-of-concept that the 3-order B-splines used in Kolmogorov-Arnold Networks (KANs) can be well approximated by Gaussian radial basis functions. Doing so leads to FastKAN, a much faster implementation of KAN which is also a radial basis function (RBF) network.
openaire   +2 more sources

Indium‐Mediated Glue‐Like Interlayer Enables Stable High‐Capacity Flexible Sodium Metal Batteries

Advanced Materials, EarlyView.
A three‐dimensional Na‐In‐S/Cu composite interlayer is constructed on a flexible current collector via an In‐mediated in situ reaction. Featuring abundant Na nucleation sites and a low diffusion barrier, this interlayer enables rapid and uniform Na deposition.
Xinyan Li, Shujing Wen, Junhua Zhou, Yanpeng Guo, Jiehua Cai, Xingyang Wang, Yongqiang Yang, Ang Ye, Can Guo, Zhaokun Wang, Qiyao Huang, M. Danny Gu, John Wang, Zijian Zheng   +13 more
wiley   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Controlling complexity of RBF networks by similarity

, 2007
Rückert U, Eickhoff R. Controlling complexity of RBF networks by similarity. In: ESANN. 2007: 181-186.Using radial basis function networks for function approximation tasks suffers from unavailable knowledge about an adequate network size.
Eickhoff, Ralf, Rückert, Ulrich
core  

A new RBF neural network with boundary value constraints

, 2009
We present a novel topology of the radial basis function (RBF) neural network, referred to as the boundary value constraints (BVC)-RBF, which is able to automatically satisfy a set of BVC.
Chen, Sheng, Hong, X., Chen, S.
core   +1 more source

Designable van der Waals Crystal for Artificial Neuronal Cell Mimicking

Advanced Materials, EarlyView.
Designable van der Waals crystal has been demonstrated for device‐scale neuronal cell mimicking. The structural similarity between ion‐channel in biological membranes and layered vdW lattices is realized with nano‐crystallization via Ar + H2S plasma sulfurization.
Jinhyoung Lee, Gunhyoung Kim, Dongho Lee, Seowoo Son, Hyunho Seok, Sihoon Son, Hyunbin Choi, Geonwook Kim, Geumji Back, Hyunkyu Kim, Chaerin Park, Junmin Ahn, Seongyun Je, Chaeyoung Im, Junil Cho, Magdalena Grzeszczyk, Seongho Kim, Eunseo Go, Hyunwoo Shim, Donghwan Choi, Muyoung Kim, Hyoeng‐U. Kim, Won‐Jun Jang, Taesung Kim   +23 more
wiley   +1 more source