Results 61 to 70 of about 173,770 (295)

Networks and the Best Approximation Property [PDF]

, 1989
Networks can be considered as approximation schemes. Multilayer networks of the backpropagation type can approximate arbitrarily well continuous functions (Cybenko, 1989; Funahashi, 1989; Stinchcombe and White, 1989).
Girosi, Federico, Poggio, Tomaso
core   +3 more sources

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution

Software
Radial basis function networks are considered a machine learning tool that can be applied on a wide series of classification and regression problems proposed in various research topics of the modern world.
Ioannis G. Tsoulos, Ioannis Varvaras, Vasileios Charilogis   +2 more
doaj   +1 more source

Improved streamflow forecasting using self-organizing radial basis function artificial neural networks [PDF]

, 2004
Streamflow forecasting has always been a challenging task for water resources engineers and managers and a major component of water resources system control. In this study, we explore the applicability of a Self Organizing Radial Basis (SORB) function to
Gupta, HV, Hsu, KL, Moradkhani, H, Sorooshian, S   +3 more
core   +1 more source

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

Reconstruction of Daily Sea Surface Temperature Based on Radial Basis Function Networks

Remote Sensing, 2017
A radial basis function network (RBFN) method is proposed to reconstruct daily Sea surface temperatures (SSTs) with limited SST samples. For the purpose of evaluating the SSTs using this method, non-biased SST samples in the Pacific Ocean (10°N–30°N, 115°
Zhihong Liao, Qing Dong, Cunjin Xue, Jingwu Bi, Guangtong Wan   +4 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  

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

A Novel Deep Reinforcement Learning Based Extended Fractal Radial Basis Function Network for State‐of‐Charge Estimation

IET Power Electronics
This paper presents a novel deep reinforcement learning based extended fractal radial basis function (DRL‐EFRBF) network for accurate state‐of‐charge (SOC) estimation in lithium iron phosphate (LiFePO4) batteries. Unlike conventional methods such as open
Syed M. Ali, Muhammad Bilal, Ayman Alharbi, Rooh ul Amin   +3 more
doaj   +1 more source

Electroencephalography Artifact Removal using Optimized Radial Basis Function Neural Networks

Majlesi Journal of Electrical Engineering
Electroencephalography (EEG) is a major clinical tool to diagnose, monitor and manage neurological disorders which is mostly affected by artifacts.
Shoorangiz Shams Shamsabad Farahani, Mohammad Mahdi Arefi, Amir Hossein Zaeri   +2 more
doaj   +1 more source