Results 1 to 10 of about 59,820 (274)
Neural networks based recognition of 3D freeform surface from 2D sketch [PDF]
, 2005 In this paper, the Back Propagation (BP) network and Radial Basis Function (RBF) neural network are employed to recognize and reconstruct 3D freeform surface from 2D freehand sketch.
Qin, SF, Sun, G, Wright, DK
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Gong-kuang zidonghua, 2014 The paper proposed a fault line selection method of small current grounding system based on wavelet de-noising and improved RBF neural network. Fault information matrix is obtained after normalization processing for maximum of absolute value of de-noised
WANG Xiaowei +3 more
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IEEE Access, 2020 With the rapid economic development, urban areas are seeing more and more vehicles, leading to frequent urban traffic congestion. To solve this problem, the forecasting of traffic parameters is essential, in which, road operating speed (hereinafter ...
Chun Ai, Lijun Jia, Mei Hong, Chao Zhang
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Application of improved PSO-RBF neural network in the synthetic ammonia decarbonization
Journal of Hebei University of Science and Technology, 2017 The synthetic ammonia decarbonization is a typical complex industrial process, which has the characteristics of time variation, nonlinearity and uncertainty, and the on-line control model is difficult to be established. An improved PSO-RBF neural network
Yongwei LI +3 more
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Complexity, 2018 The neural network has the advantages of self-learning, self-adaptation, and fault tolerance. It can establish a qualitative and quantitative evaluation model which is closer to human thought patterns.
Tiantian Luan +3 more
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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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Integrated neural network model with pre-RBF kernels
Science Progress, 2021 To improve the network performance of radial basis function (RBF) and back-propagation (BP) networks on complex nonlinear problems, an integrated neural network model with pre-RBF kernels is proposed.
Hui Wen +3 more
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Surface profile prediction and analysis applied to turning process [PDF]
, 2008 An approach for the prediction of surface profile in turning process using Radial Basis Function (RBF) neural networks is presented. The input parameters of the RBF networks are cutting speed, depth of cut and feed rate.
COSTES, Jean-Philippe, LU, Chen
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