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Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive

Faezehossadat KHADEMI,Mahmoud AKBARI,Sayed Mohammadmehdi JAMAL,Mehdi NIKOO

Frontiers of Structural and Civil Engineering 2017, Volume 11, Issue 1,   Pages 90-99 doi: 10.1007/s11709-016-0363-9

Abstract: experimental results, three different models of multiple linear regression model (MLR), artificial neuralnetwork (ANN), and adaptive neuro-fuzzy inference system (ANFIS) are established, trained, and tested

Keywords： concrete     28 days compressive strength     multiple linear regression     artificial neural network     ANFIS     sensitivity    

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Research on fuzzy neural network control method for high-frequency vacuum drying of wood

Jiang Bin,Sun Liping,Cao Jun and Zhou Zheng

Strategic Study of CAE 2014, Volume 16, Issue 4,   Pages 17-20

Abstract: On the basis of theoretical analysis with high frequency in wood vacuum drying process，the fuzzy controllerand fuzzy neural network controller of wood drying are designed in view of the neural network methodThe simulation experiment results show that fuzzy neural network control is better，such as the temperature

Keywords： high-frequency vacuum     wood drying     fuzzy neural network    

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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 functionapproaching ability, their combination can produce a neural network model with good intelligibilityThen, these rules are applied to constructing neural cell numbers and relative parameters in fuzzy neuralnetwork.

Keywords： fuzzy neural network     rough set     acquire rule     function approaching    

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Predicting the yield of pomegranate oil from supercritical extraction using artificial neural networksand an adaptive-network-based fuzzy inference system

J. Sargolzaei, A. Hedayati Moghaddam

Frontiers of Chemical Science and Engineering 2013, Volume 7, Issue 3,   Pages 357-365 doi: 10.1007/s11705-013-1336-3

Abstract: Several simulation systems including a back-propagation neural network (BPNN), a radial basis functionneural network (RBFNN) and an adaptive-network-based fuzzy inference system (ANFIS) were tested and

Keywords： oil recovery     artificial intelligence     extraction     neural networks     supercritical extraction    

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A Fuzzy Neural Network Based on Rough Sets and Its Applications to Chemical Fiber Production

Chen Shuangye,Yi Jikai

Strategic Study of CAE 2001, Volume 3, Issue 12,   Pages 42-46

Abstract:

A fuzzy neural network based on rough sets is presented in this paper., then the structure and model are designed according these rules, and then the model is trained by neuralnetwork technique.

Keywords： rough sets     fuzzy logic     neural network     rules extracted    

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Intelligent diagnosis methods for plant machinery

Huaqing WANG, Peng CHEN, Shuming WANG,

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 1,   Pages 118-124 doi: 10.1007/s11465-009-0084-z

Abstract: This paper reports several intelligent diagnostic approaches based on artificial neural network and fuzzyalgorithm for plant machinery, such as the diagnosis method using the wavelet transform, rough sets, and fuzzyneural network; the diagnosis method based on the sequential inference and fuzzy neural network; thecertainty factor model; and the diagnosis method on the basis of the adaptive filtering technique and fuzzyneural network.

Keywords： intelligent diagnosis     neural network     fuzzy algorithm     adaptive filtering     plant machinery    

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Comparative study of various artificial intelligence approaches applied to direct torque control of induction motor drives

Moulay Rachid DOUIRI, Mohamed CHERKAOUI

Frontiers in Energy 2013, Volume 7, Issue 4,   Pages 456-467 doi: 10.1007/s11708-013-0264-8

Abstract: of induction motor drive to replace conventional hysteresis comparators and selection table, namely fuzzylogic, artificial neural network and adaptive neuro-fuzzy inference system (ANFIS).The simulated results obtained demonstrate the feasibility of the adaptive network-based fuzzy inferenceCompared with the classical direct torque control, fuzzy logic based direct torque control (FL-DTC),and neural networks based direct torque control (NN-DTC), the proposed ANFIS-based scheme optimizes the

Keywords： adaptive neuro-fuzzy inference system (ANFIS)     artificial neural network     direct torque control (DTC)     fuzzy    

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Multiscale computation on feedforward neural network and recurrent neural network

Bin LI, Xiaoying ZHUANG

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 6,   Pages 1285-1298 doi: 10.1007/s11709-020-0691-7

Abstract: The neural networks can be used to construct fully decoupled approaches in nonlinear multiscale methodsThis article intends to model the multiscale constitution using feedforward neural network (FNN) andrecurrent neural network (RNN), and appropriate set of loading paths are selected to effectively predict

Keywords： multiscale method     constitutive model     feedforward neural network     recurrent neural network    

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Research on On-line Detecting Method and Key Technologies for Part Quality (Dimension and Surface Roughness)

Chen Aidi,Wang Xinyi

Strategic Study of CAE 2000, Volume 2, Issue 12,   Pages 73-77

Abstract: of methods and features of on-line detecting of part dimension and surface roughness, an artificial neuralnetwork system for on-line detecting of part dimension and a fuzzy neural network system for on-line

Keywords： on-line detecting     neural network     fuzzy neural network     dimension precision     surface roughness    

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Pattern Recognition With Fuzzy Central Clustering Algorithms

Zen Huanglin,Yuan Hui,Liu Xiaofang

Strategic Study of CAE 2004, Volume 6, Issue 11,   Pages 33-37

Abstract: >Based on optimization of constrained nonlinear programming, an approach of clustering center and a fuzzyAn unsupervised algorithm with recursive expression and a fuzzy central cluster neural network are suggestedThe fuzzy central cluster neural network proposed here can realize crisp decision or fuzzy decision in

Keywords： fuzzy sets     central cluster     pattern recognition     neural network    

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Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 2,   Pages 149-156 doi: 10.1007/s11465-010-0008-y

Abstract: In this paper, an SPC method based on a fuzzy adaptive resonance theory (ART) neural network is presentedThe fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processesbased on the classification on the histograms, which shows that the fuzzy ART neural network can adaptivelythe same time, combined with spectrum analysis of the autoregressive model of quality parameters, the fuzzyART neural network can also be utilized to adaptively detect the abnormal patterns in the control chart

Keywords： statistical process control (SPC)     fuzzy adaptive resonance theory (ART)     histogram     control chart     time    

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A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 2, doi: 10.1007/s11465-022-0673-7

Abstract: Convolutional neural network (CNN) has achieved remarkable applications in fault diagnosis.

Keywords： deep reinforcement learning     hyper parameter optimization     convolutional neural network     fault diagnosis    

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Novel interpretable mechanism of neural networks based on network decoupling method

Frontiers of Engineering Management 2021, Volume 8, Issue 4,   Pages 572-581 doi: 10.1007/s42524-021-0169-x

Abstract: The lack of interpretability of the neural network algorithm has become the bottleneck of its wide applicationnetwork.Result shows that a simple linear mapping relationship exists between network structure and network behaviorin the neural network with high-dimensional and nonlinear characteristics.which can further expand and enrich the interpretable mechanism of artificial neural network in the future

Keywords： neural networks     interpretability     dynamical behavior     network decouple    

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Deep convolutional neural network for multi-level non-invasive tunnel lining assessment

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 2,   Pages 214-223 doi: 10.1007/s11709-021-0800-2

Abstract: Such strategy leverages the high capacity of convolutional neural networks to identify and classify potential

Keywords： concrete structure     GPR     damage classification     convolutional neural network     transfer learning    

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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(FBF) neural network classifier is proposed in this paper. With the new sample set the FBF network can be trained to track the variable clustering boundary

Keywords： fuzzy basis function     self-learning     fault diagnosis    

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Title Author Date Type Operation

Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive

Faezehossadat KHADEMI,Mahmoud AKBARI,Sayed Mohammadmehdi JAMAL,Mehdi NIKOO

Journal Article

Research on fuzzy neural network control method for high-frequency vacuum drying of wood

Jiang Bin,Sun Liping,Cao Jun and Zhou Zheng

Journal Article

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

Huang Xianming,Yi Jikai

Journal Article

Predicting the yield of pomegranate oil from supercritical extraction using artificial neural networksand an adaptive-network-based fuzzy inference system

J. Sargolzaei, A. Hedayati Moghaddam

Journal Article

A Fuzzy Neural Network Based on Rough Sets and Its Applications to Chemical Fiber Production

Chen Shuangye,Yi Jikai

Journal Article

Intelligent diagnosis methods for plant machinery

Huaqing WANG, Peng CHEN, Shuming WANG,

Journal Article

Comparative study of various artificial intelligence approaches applied to direct torque control of induction motor drives

Moulay Rachid DOUIRI, Mohamed CHERKAOUI

Journal Article

Multiscale computation on feedforward neural network and recurrent neural network

Bin LI, Xiaoying ZHUANG

Journal Article

Research on On-line Detecting Method and Key Technologies for Part Quality (Dimension and Surface Roughness)

Chen Aidi,Wang Xinyi

Journal Article

Pattern Recognition With Fuzzy Central Clustering Algorithms

Zen Huanglin,Yuan Hui,Liu Xiaofang

Journal Article

Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

Journal Article

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Journal Article

Novel interpretable mechanism of neural networks based on network decoupling method

Journal Article

Deep convolutional neural network for multi-level non-invasive tunnel lining assessment

Journal Article

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

Xu Feiyun,Zhong Binglin,Huang Ren

Journal Article