Results 51 to 60 of about 274,124 (332)

Modeliranje 3D-ploskev z nevronskimi mrežami z radialnimi baznimi aktivacijskimi funkcijami ( = The employment of a radial basis function network for 3D surface modelling) [PDF]

Geodetski Vestnik, 2016
Determination of the mathematical model of elevation computation is based on a discrete data set, which could be used for elevation modelling.
Polona Pavlovčič Prešeren, Bojan Stopar, Oskar Sterle   +2 more
doaj   +1 more source

Tourism demand forecasting with different neural networks models [PDF]

, 2014
This paper aims to compare the performance of different Artificial Neural Networks techniques for tourist demand forecasting. We test the forecasting accuracy of three different types of architectures: a multi-layer perceptron, a radial basis function ...
Clavería González, Óscar, Monte Moreno, Enric, Torra Porras, Salvador   +2 more
core  

Microstructure Design of Steel‐Spinel Composites via Spark Plasma Sintering Process

Advanced Engineering Materials, EarlyView.
This study illustrates how spark plasma sintering at reduced oxygen partial pressure enables controlled formation of steel‐spinel composites through tailored redox reactions and cation exchange. Comparison of the MgO–Fe2O3, steel–(MgO+Cr2O3), and steel–(MgO+Fe2O3) systems shows how oxygen activity and interface chemistry govern spinel formation, phase ...
Mahnaz Mehdizadehlima, Christian Schimpf, Stefan Martin, Olga Fabrichnaya, David Rafaja   +4 more
wiley   +1 more source

基于AR模型和径向基神经网络的滚动轴承故障诊断

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  

An Offline Weighted-Bagging Data-Driven Evolutionary Algorithm with Data Generation Based on Clustering

Mathematics, 2023
In recent years, a variety of data-driven evolutionary algorithms (DDEAs) have been proposed to solve time-consuming and computationally intensive optimization problems.
Zongliang Guo, Sikai Lin, Runze Suo, Xinming Zhang   +3 more
doaj   +1 more source

A Connection Between GRBF and MLP [PDF]

, 1992
Both multilayer perceptrons (MLP) and Generalized Radial Basis Functions (GRBF) have good approximation properties, theoretically and experimentally. Are they related?
Girosi, Federico, Maruyama, Minoru, Poggio, Tomaso   +2 more
core  

Enhanced Strength and Corrosion Resistance of Ti‐13Nb‐12Ta‐10Zr‐4Sn Alloy by Aging Treatment

Advanced Engineering Materials, EarlyView.
This work systematically investigates the effect of aging treatment on mechanical properties and corrosion behavior of vacuum arc‐melted Ti‐13Nb‐12Ta‐10Zr‐4Sn alloy. Owing to the increased α″ martensite, strength and corrosion resistance were significantly enhanced by aging treatment.
Yuhua Li, Rong Zhao, Qian Zhang, Haojie Wang, Yujing Liu, Lai‐Chang Zhang   +5 more
wiley   +1 more source

Intermolecular Interactions as Driving Force of Increasing Multiphoton Absorption in a Perylene Diimide‐Based Coordination Polymer

Advanced Functional Materials, EarlyView.
This study uncovers the unexplored role of intermolecular interactions in multiphoton absorption in coordination polymers. By analyzing [Zn2tpda(DMA)2(DMF)0.3], it shows how the electronic coupling of the chromophores and confinement in the MOF enhance two‐and three‐photon absorption.
Simon Nicolas Deger, Anna Mauri, Yang Cui, Sebastian Josef Weishäupl, Ali Deniz Özdemir, Hamad Syed, Aleksandr Ovsianikov, Wolfgang Wenzel, Alexander Pöthig, Jürgen Hauer, Mariana Kozlowska, Roland Augustinus Fischer   +11 more
wiley   +1 more source

Magnetic dot arrays modeling via the system of the radial basis function networks

, 2002
Two dimensional square lattice general model of the magnetic dot array is introduced. In this model the intradot self-energy is predicted via the neural network and interdot magnetostatic coupling is approximated by the collection of several dipolar ...
Abraham, Aharoni, Aharoni, Berkov, Brankov, Brown, Chou, Demand, Denis Horváth, Fernandez, Gushlienko, Ivo Vávra, Jeppesen, Jones, Kirkpatrick, Kodama, Kordonsky, Labbé, Lejeune, Liebovitch, Luttinger, Martin Gmitra, Mattheis, Metropolis, Metzler, Miles, Nussbaum, Pardavi-Horvath, Prakash, Saliah, Schabes, Scheinfein, Schrefl, Shinjo, Stamps, Vadmedenko, Visone, Wu   +37 more
core   +1 more source

The effect of several parameters on radial basis function networks for time series prediction [PDF]

, 2006
In this study, several radial basis function networks are compared according to their approximation ability in time series forecasting problems. Optimal values for the tested parameters are obtained using computer simulation runs.
Uysal, Mitat
core   +1 more source