Results 71 to 80 of about 99,944 (264)
Organisms modeling: The question of radial basis function networks
ITM Web of Conferences, 2014 There exists usually a gap between bio-inspired computational techniques and what biologists can do with these techniques in their current researches. Although biology is the root of system-theory and artifical neural networks, computer scientists are ...
Muzy Alexandre +2 more
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Advanced Engineering Materials, EarlyView.Residual adhesive after electrode loading in adhesive‐assisted resistance spot welding is quantified through a traceable experimental‐to‐digital workflow. Chromatic confocal topography provides calibrated surface‐height data, while OpenCV detects the electrode imprint and integrates adhesive height into comparable volume metrics.
Sung‐Min Wi, Jiangdong Zhao
wiley +1 more source
Advanced Engineering Materials, EarlyView.We apply a foundational machine‐learning interatomic potential based on the graph atomic cluster expansion (GRACE) to simulate the commercial Ni‐based single‐crystal superalloy CMSX‐4. Hybrid Monte‐Carlo/molecular dynamics sampling resolves short‐range order in the γ phase and L12 sublattice occupancies in the γ’ phase and connects them to stacking ...
Aditya Vishwakarma +4 more
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On Comparison between Radial Basis Function and Wavelet Basis Functions Neural Networks
Ibn Al-Haitham Journal for Pure and Applied Sciences, 2017 In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space.
L.N.M. Tawfiq, T.A.M. Rashid
doaj
MathematicsGaussian Radial Basis Function Kernels are the most-often-employed kernel function in artificial intelligence for providing the optimal results in contrast to their respective counterparts.
Himanshu Singh
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Radial basis functions under tension
Journal of Approximation Theory, 2004 Radial basis function interpolation is one of the prime methods for interpolation to scattered data in more than one dimension. Both for application and for the theory, so-called native spaces associated with the radial basis functions are very important.
Abderrahman Bouhamidi +1 more
openaire +2 more sources
Laser‐Induced Graphene from Waste Almond Shells
Advanced Functional Materials, EarlyView.Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova +9 more
wiley +1 more source
Molecular Adsorbing Host•Guest (MAHG) Crystals: A New Paradigm for Porous Materials?
Advanced Functional Materials, EarlyView.Networking! Introduction of guest molecules in macrocycles before crystallization profoundly influences the material obtained in terms of structure and function. Beside simplicity and porous space improvement, this approach is endowed with a huge potential given the myriad of potential guest molecules that can be used to tune this burgeoning class of ...
Ingrid Suzana +4 more
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Jixie chuandong, 2004 Radial basis function neural network is a type of three-layer feedforward non-linear network. It has many good properties, such as powerful ability for function approximation, classification.
陆爽, 侯跃谦, 田野
doaj
Advanced Functional Materials, EarlyView.In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa +19 more
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