Resource Type

Journal Article 8

Year

2019 1

2017 1

2008 1

2007 1

2005 1

2004 2

Keywords

RBF neural networks 3

AR model 1

BP neural networks 1

Grey wolf optimizer 1

Optimization 1

RBF 1

RBFs 1

Radial basis function network 1

Swarm intelligence 1

artificial neural network (ANN) 1

central high resolution schemes 1

deformation forecast 1

deformation of wall rock 1

dimensional analysis 1

forecasting 1

generalized thermoelasticity 1

groundwater 1

higher order accuracy 1

hydrogeological parameter 1

multi-arch tunnel 1

open ︾

Search scope:

排序： Display mode:

A Forecasting Method for Tunnel Surrounding Rock Deformation Using RBF Neural Networks

Zhang Junyan,Feng Shouzhong,Liu Donghai

Strategic Study of CAE 2005, Volume 7, Issue 10,   Pages 87-90

Abstract:

Owing to the difficulty of traditional multi-variable regression methods to represent the surrounding rock deformation curve with inflexion points, a method for forecasting tunnel surrounding rock deformation using radial basis function neural networks is presented. This method not only can be utilized to approximate the complex deformation curves, but also has higher convergence speed and better globally-searching ability than those using BP neural networks. An example is given to show the effectiveness and practicability of this method.

Keywords： RBF neural networks     tunnel construction     surrounding rock deformation     forecasting    

HTML PDF Collect

RBF-ANN-Based forecast method of transmutation of wall rock on multi-arch tunne

Xiao Zhiwang,Zhong Denghua

Strategic Study of CAE 2008, Volume 10, Issue 7,   Pages 77-81

Abstract:

The key of forecasting transmutation of wall rock correctly is to construct the reasonable mathematics model of time-distance curve from measuring data when distorting, which is hard to describe accurately with traditional method of recursive analysis. According to the characteristics of feed forward neural network of radial basis function to construct the forecast model of deformation of wall rock in multi-arch tunnel and cllso uses Matlab tool to solve the optimal problem. The engineering case at the end of this paper validates the method. For its fast solving the problem,more optimal results,and better forecasting effects,this method shows its advantages and feasibility.

Keywords： multi-arch tunnel     deformation of wall rock     deformation forecast     radial basis function (RBF)     artificial    

HTML PDF Collect

Hydrogeological Parameter Identification Based on the Radial Basis Function Neural Networks

Zhang Junyan,Wei Lianwei,Han Weixiu,Shao Jingli,Cui Yali,Zhang Jianli

Strategic Study of CAE 2004, Volume 6, Issue 8,   Pages 74-78

Abstract: limit of identifying the parameter by traditional methods, the radial basis function neural networks (RBF

Keywords： groundwater     hydrogeological parameter     radial basis function (RBF) neural networks     BP neural networks    

HTML PDF Collect

Reliability-based design optimization of offshore wind turbine support structures using RBF surrogate

Frontiers of Structural and Civil Engineering   Pages 1086-1099 doi: 10.1007/s11709-023-0976-8

Abstract: Reliability-based design optimization of offshore wind turbine support structures using RBF surrogate

Keywords： RBF     surrogate model     turbine support structures    

HTML PDF Collect

Multiscale RBF-based central high resolution schemes for simulation of generalized thermoelasticity problems

Hassan YOUSEFI, Alireza TAGHAVI KANI, Iradj MAHMOUDZADEH KANI

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 2,   Pages 429-455 doi: 10.1007/s11709-018-0483-5

Abstract: accurate simulations, the multiresolution–based grid adaptation approach is then integrated with the RBF-basedThere, performance of the adaptive RBF-based formulation is compared with that of the adaptive Kurganov-Tadmor

Keywords： central high resolution schemes     RBFs     higher order accuracy     generalized thermoelasticity     multiresolution-based adaptation    

HTML PDF Collect

Fault Pattern Recognition of Rolling Bearing Based on Radial Basis Function Neural Networks

Lu Shuang,Zhang Zida,Li Meng

Strategic Study of CAE 2004, Volume 6, Issue 2,   Pages 56-60

Abstract:

Radial basis function neural network is a type of three — layer feedforward network. It has many good properties, such as powerful ability for function approximation, classification and learning rapidly. In this paper, in the light of the merit of radial basis function neural network and on the basis of the feature analysis of vibration signal of rolling bearing, AR model is presented by using time series method. Radial basis function neural networks is established based on AR model parameters. In the light of the theory of radial basis function neural networks, fault pattern of rolling bearing is recognized correspondingly. Theory and experiment show that the recognition of fault pattern of rolling bearing based on radial basis function neural networks theory is available and its precision is high.

Keywords： rolling bearing     vibration signal     AR model     RBF neural networks     pattern recognition    

HTML PDF Collect

Penetration Depth of Projectiles Into Concrete Using Artificial Neural Network

Li Jianguang,Li Yongchi,Wang Yulan

Strategic Study of CAE 2007, Volume 9, Issue 8,   Pages 77-81

Abstract:  Moreover,  a satisfied output about penetration depth from RBF neural network is gotten by

Keywords： dimensional analysis     penetration depth of projectiles into concrete     nonlinear mapping relation     RBF    

HTML PDF Collect

An optimized grey wolf optimizer based on a mutation operator and eliminating-reconstructing mechanism and its application Article

Xiao-qing ZHANG, Zheng-feng MING

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1705-1719 doi: 10.1631/FITEE.1601555

Abstract: the global optimization experiment of 13 standard continuous functions and a radial basis function (RBF

Keywords： Swarm intelligence     Grey wolf optimizer     Optimization     Radial basis function network    

HTML PDF Collect

Title Author Date Type Operation

A Forecasting Method for Tunnel Surrounding Rock Deformation Using RBF Neural Networks

Zhang Junyan,Feng Shouzhong,Liu Donghai

Journal Article

RBF-ANN-Based forecast method of transmutation of wall rock on multi-arch tunne

Xiao Zhiwang,Zhong Denghua

Journal Article

Hydrogeological Parameter Identification Based on the Radial Basis Function Neural Networks

Zhang Junyan,Wei Lianwei,Han Weixiu,Shao Jingli,Cui Yali,Zhang Jianli

Journal Article

Reliability-based design optimization of offshore wind turbine support structures using RBF surrogate

Journal Article

Multiscale RBF-based central high resolution schemes for simulation of generalized thermoelasticity problems

Hassan YOUSEFI, Alireza TAGHAVI KANI, Iradj MAHMOUDZADEH KANI

Journal Article

Fault Pattern Recognition of Rolling Bearing Based on Radial Basis Function Neural Networks

Lu Shuang,Zhang Zida,Li Meng

Journal Article

Penetration Depth of Projectiles Into Concrete Using Artificial Neural Network

Li Jianguang,Li Yongchi,Wang Yulan

Journal Article

An optimized grey wolf optimizer based on a mutation operator and eliminating-reconstructing mechanism and its application

Xiao-qing ZHANG, Zheng-feng MING

Journal Article