Results 31 to 40 of about 1,355,935 (279)
Finite Element Model Modification of Arch Bridge Based on Radial Basis Function Neural Network [PDF]
E3S Web of Conferences, 2019 Compared with other neural networks, Radial Basis Function (RBF) neural network has the advantages of simple structure and fast convergence. As long as there are enough hidden layer nodes in the hidden layer, it can approximate any non-linear function ...
Chen Tongqing +4 more
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A new type of fault diagnosis method of asynchronous motor
Gong-kuang zidonghua, 2014 In view of problem of difficult parameters determination existed in fault diagnosis method of asynchronous motor based on RBF neural network, the paper proposed a fault diagnosis method of asynchronous motor based on RBF neural network optimized by ...
GOU Xijin, XU Jinxia, KONG Lili
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An online self-adaptive RBF network algorithm based on the Levenberg-Marquardt algorithm
Applied Artificial Intelligence, 2022 Aiming at the problem that the Levenberg-Marquardt (LM) algorithm can not train online radial basis function (RBF) neural network and the deficiency in the RBF network structure design methods, this paper proposes an online self-adaptive algorithm for ...
ZhaoZhao Zhang +3 more
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Nanotechnology Reviews, 2022 In this study, we investigated the mechanical properties and chloride ion permeation resistance of geopolymer mortars based on fly ash modified with nano-SiO2 (NS) and polyvinyl alcohol (PVA) fiber and metakaolin (MK) at dose levels of 0–1.2% for PVA ...
Zhang Xuemei +5 more
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Target maneuver trajectory prediction based on RBF neural network optimized by hybrid algorithm
, 2021 Target maneuver trajectory prediction plays an important role in air combat situation awareness and threat assessment. To solve the problem of low prediction accuracy of the traditional prediction method and model, a target maneuver trajectory prediction
Xi Zhifei +4 more
semanticscholar +1 more source
Upset Prediction in Friction Welding Using Radial Basis Function Neural Network
Advances in Materials Science and Engineering, 2013 This paper addresses the upset prediction problem of friction welded joints. Based on finite element simulations of inertia friction welding (IFW), a radial basis function (RBF) neural network was developed initially to predict the final upset for a ...
Wei Liu +3 more
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Modeling and neural sliding mode control of mems triaxial gyroscope
Advances in Mechanical Engineering, 2022 In this paper, a neural sliding mode control approach is developed to adjust the sliding gain using a radial basis function (RBF) neural network (NN) for the tracking control of Microelectromechanical Systems (MEMS) triaxial vibratory gyroscope.
Yunmei Fang +3 more
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Frontiers in Energy Research, 2022 In this study, a cladding surface temperature prediction method based on an adaptive RBF neural network was proposed. This method can significantly improve the accuracy and efficiency of the thermal safety evaluation of the lead–bismuth fast reactor ...
Hong Wu +4 more
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Viscosity Prediction of Different Ethylene Glycol/Water Based Nanofluids Using a RBF Neural Network
Applied Sciences, 2017 In this study, a radial basis function (RBF) neural network with three-layer feed forward architecture was developed to effectively predict the viscosity ratio of different ethylene glycol/water based nanofluids.
Ningbo Zhao, Zhiming Li
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Frontiers in Earth Science, 2023 Risk assessment is critical to ensure the safe operation of oil and gas pipeline systems. The core content of such risk assessment is to determine the failure probability of the pipelines quantitatively and accurately.
Lexin Zhao +3 more
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