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Research on An On-line Tracking Self-learning Algorithm for Fuzzy Basis Function Neural Network

Xu Feiyun,Zhong Binglin,Huang Ren

Strategic Study of CAE 2007, Volume 9, Issue 11,   Pages 48-53

Abstract:

An on-line tracking self-learning algorithm for fuzzy basis function

Keywords： fuzzy basis function     self-learning     fault diagnosis    

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An efficient stochastic dynamic analysis of soil media using radial basis function artificial neural

P. ZAKIAN

Frontiers of Structural and Civil Engineering 2017, Volume 11, Issue 4,   Pages 470-479 doi: 10.1007/s11709-017-0440-8

Abstract: Since a lot of engineering problems are along with uncertain parameters, stochastic methods are of great importance for incorporating random nature of a system property or random nature of a system input. In this study, the stochastic dynamic analysis of soil mass is performed by finite element method in the frequency domain. Two methods are used for stochastic analysis of soil media which are spectral decomposition and Monte Carlo methods. Shear modulus of soil is considered as a random field and the seismic excitation is also imposed as a random process. In this research, artificial neural network is proposed and added to Monte Carlo method for sake of reducing computational effort of the random analysis. Then, the effects of the proposed artificial neural network are illustrated on decreasing computational time of Monte Carlo simulations in comparison with standard Monte Carlo and spectral decomposition methods. Numerical verifications are provided to indicate capabilities, accuracy and efficiency of the proposed strategy compared to the other techniques.

Keywords： stochastic analysis     random seismic excitation     finite element method     artificial neural network     frequency domain analysis     Monte Carlo simulation    

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Improved approach to quality function deployment based on Pythagorean fuzzy sets and application to assembly

Huchang LIAO, Yinghan CHANG, Di WU, Xunjie GOU

Frontiers of Engineering Management 2020, Volume 7, Issue 2,   Pages 196-203 doi: 10.1007/s42524-019-0038-z

Abstract: Quality function deployment (QFD) is an effective method that helps companies analyze customer requirementsTo increase the effectiveness of QFD, we propose an improved method based on Pythagorean fuzzy sets (To determine the exact score of each PFS in the evaluation matrix, we develop an improved score function

Keywords： quality function deployment     Pythagorean fuzzy sets     group consensus     combined weights     assembly robot design    

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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: MR-GWO is applied to the global optimization experiment of 13 standard continuous functions and a radial basisfunction (RBF) network approximation experiment.

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

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Approximating Characteristics of Fuzzy Systems With Arbitrary Membership Function

Zhang Zhao,Pei Yanling,Zheng Aihong

Strategic Study of CAE 2005, Volume 7, Issue 8,   Pages 47-50

Abstract:

While quadrilateral membership function is used as general membership function, Stone-Weierstrassany continuous function on a compact set.It is a generalization for theory of basic fuzzy systems approximating any continuous non-linear functionThe performance of fuzzy systems to approximate random non-linear function is the theoretical basis offuzzy system's application in system identification.

Keywords： fuzzy system     membership function     approximation    

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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: With the limit of identifying the parameter by traditional methods, the radial basis function neural

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

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Adaptive construction of multiwavelet basis function and its applications for mechanical fault diagnosis

He Zhengjia,Sun Hailiang,Zi Yanyang

Strategic Study of CAE 2011, Volume 13, Issue 10,   Pages 83-92

Abstract: The paper studied the principle of inner product transform of dynamic signals and basis functions, proposedseveral construction methods of adaptive multiwavelet basis functions,and improved several multiwavelet

Keywords： mechanical fault diagnosis     principle of inner product transform     adaptive basis function     multiwavelet    

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A Method of Constructing Fuzzy Neural Network Based on Rough Set Theory

Huang Xianming,Yi Jikai

Strategic Study of CAE 2004, Volume 6, Issue 4,   Pages 44-50

Abstract:

A new method of constructing fuzzy neural network is presented and Rough set theory is applied toSince Rough set theory has strong numeric analyzing ability and fuzzy neural network has exact functionThen, these rules are applied to constructing neural cell numbers and relative parameters in fuzzy neuralAlso in this paper, an example of nonlinear function approaching is discussed and the feasibility of

Keywords： fuzzy neural network     rough set     acquire rule     function approaching    

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Fuzzy Programming Based Modeling of Production Scheduling of Batch Processes

Zhang Hong,Li Chiqiang

Strategic Study of CAE 2004, Volume 6, Issue 10,   Pages 65-70

Abstract: method based on fuzzy programming for batching production processes and offers a modeling method withfuzzy coefficients.Two fuzzy algorithms based on genetic algorithm, i. e. , fuzzy simulation and SFA algorithm, are adoptedto solve the fuzzy model.The selection of membership function is flexible, and a proper expression of fuzziness is adopted.

Keywords： production scheduling     fuzzy programming     batching production processes     membership function    

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A Robust Tolerance Design Method Based on Fuzzy Quality Loss

CAO Yan-long, MAO Jian, YANG Jiang-xin, WU Zhao-tong, WU Li-qun

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 1,   Pages 101-105 doi: 10.1007/s11465-005-0010-y

Abstract: Based on the analysis of fuzzy factors in tolerance design and the limitations of the traditional Taguchisquared quality loss function, a fuzzy quality loss function model utilizing fuzzy theory was introducedConcepts on fuzzy quality loss and fuzzy quality loss cost were proposed in the model.The characteristics of the new model and the advantages over the traditional Taguchi quality loss functionA robust tolerance design model using a fuzzy quality loss function was proposed.

Keywords： impact     function     robust tolerance     suitable     quality    

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Genetic basis of adult-onset nephrotic syndrome and focal segmental glomerulosclerosis

Jian Liu, Weiming Wang

Frontiers of Medicine 2017, Volume 11, Issue 3,   Pages 333-339 doi: 10.1007/s11684-017-0564-1

Abstract:

Nephrotic syndrome (NS) is one of the most common glomerular diseases with signs of nephrosis, heavy proteinuria, hypoalbuminemia, and edema. Dysfunction of glomerular filtration barrier causes protein loss through the kidneys. Focal segmental glomerulosclerosis (FSGS) accounts for nearly 20% of NS among children and adults. Adult-onset FSGS/NS is often associated with low response to steroid treatment and immunosuppressive medication and poor renal survival. Several genes involved in NS and FSGS have been identified by linkage analysis and next-generation sequencing. Most of these genes encode proteins and are highly expressed in glomerular podocytes, which play crucial roles in slit-diaphragm signaling, regulation of actin cytoskeleton dynamics and maintenance of podocyte integrity, and cell–matrix interactions. In this review, we focus on the recently identified genes in the adult-onset NS and FSGS and discuss clinical significance of screening of these genes.

Keywords： nephrotic syndrome     focal segmental glomerulosclerosis     genetic    

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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.In this paper, in the light of the merit of radial basis function neural network and on the basis ofRadial 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 bearingfunction neural networks theory is available and its precision is high.

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

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Core designing of a new type of TVS-2M FAs: neutronics and thermal-hydraulics design basis limits

Saeed GHAEMI, Farshad FAGHIHI

Frontiers in Energy 2021, Volume 15, Issue 1,   Pages 256-278 doi: 10.1007/s11708-018-0583-x

Abstract: One of the most important aims of this study is to improve the core of the current VVER reactors to achieve more burn-up (or more cycle length) and more intrinsic safety. It is an independent study on the Russian new proposed FAs, called TVS-2M, which would be applied for the future advanced VVERs. Some important aspects of neutronics as well as thermal hydraulics investigations (and analysis) of the new type of Fas are conducted, and results are compared with the standards PWR CDBL. The TVS-2M FA contains gadolinium-oxide which is mixed with UO (for different Gd densities and U-235 enrichments which are given herein), but the core does not contain BARs. The new type TVS-2M Fas are modeled by the SARCS software package to find the PMAXS format for three states of CZP and HZP as well as HFP, and then the whole core is simulated by the PARCS code to investigate transient conditions. In addition, the WIMS-D5 code is suggested for steady core modeling including TVS-2M FAs and/or TVS FAs. Many neutronics aspects such as the first cycle length (first cycle burn up in terms of MW d/kgU), the critical concentration of boric acid at the BOC as well as the cycle length, the axial, and radial power peaking factors, differential and integral worthy of the most reactive CPS-CRs, reactivity coefficients of the fuel, moderator, boric acid, and the under-moderation estimation of the core are conducted and benchmarked with the PWR CDBL. Specifically, the burn-up calculations indicate that the 45.6 d increase of the first cycle length (which corresponds to 1.18 MW d/kgU increase of burn-up) is the best improving aim of the new FA type called TVS-2M. Moreover, thermal-hydraulics core design criteria such as MDNBR (based on W3 correlation) and the maximum of fuel and clad temperatures (radially and axially), are investigated, and discussed based on the CDBL.

Keywords： TVS-2M FAs     core design basis limits     VVER-1000     analysis     mixture of uranium-gadolinium oxides fuels     thermal-hydraulics    

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Developing effective tumor vaccines: basis, challenges and perspectives

XU Qingwen, CHEN Weifeng

Frontiers of Medicine 2007, Volume 1, Issue 1,   Pages 11-19 doi: 10.1007/s11684-007-0003-9

Abstract: A remarkable advance in tumor immunology during the last decade is the elucidation of the antigenic basis

Keywords： development     conventional     identification     elucidation     Successful immunotherapy    

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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: According to the characteristics of feed forward neural network of radial basis function to construct

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

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Title Author Date Type Operation

Research on An On-line Tracking Self-learning Algorithm for Fuzzy Basis Function Neural Network

Xu Feiyun,Zhong Binglin,Huang Ren

Journal Article

An efficient stochastic dynamic analysis of soil media using radial basis function artificial neural

P. ZAKIAN

Journal Article

Improved approach to quality function deployment based on Pythagorean fuzzy sets and application to assembly

Huchang LIAO, Yinghan CHANG, Di WU, Xunjie GOU

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

Approximating Characteristics of Fuzzy Systems With Arbitrary Membership Function

Zhang Zhao,Pei Yanling,Zheng Aihong

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

Adaptive construction of multiwavelet basis function and its applications for mechanical fault diagnosis

He Zhengjia,Sun Hailiang,Zi Yanyang

Journal Article

A Method of Constructing Fuzzy Neural Network Based on Rough Set Theory

Huang Xianming,Yi Jikai

Journal Article

Fuzzy Programming Based Modeling of Production Scheduling of Batch Processes

Zhang Hong,Li Chiqiang

Journal Article

A Robust Tolerance Design Method Based on Fuzzy Quality Loss

CAO Yan-long, MAO Jian, YANG Jiang-xin, WU Zhao-tong, WU Li-qun

Journal Article

Genetic basis of adult-onset nephrotic syndrome and focal segmental glomerulosclerosis

Jian Liu, Weiming Wang

Journal Article

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

Lu Shuang,Zhang Zida,Li Meng

Journal Article

Core designing of a new type of TVS-2M FAs: neutronics and thermal-hydraulics design basis limits

Saeed GHAEMI, Farshad FAGHIHI

Journal Article

Developing effective tumor vaccines: basis, challenges and perspectives

XU Qingwen, CHEN Weifeng

Journal Article

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

Xiao Zhiwang,Zhong Denghua

Journal Article