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Estimating moment capacity of ferrocement members using self-evolving network

Abdussamad ISMAIL

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 4,   Pages 926-936 doi: 10.1007/s11709-019-0527-5

Abstract: In this paper, an empirical model based on self-evolving neural network is proposed for predicting theFurther comparisons with other data mining techniques including the back-propagation network, the adaptive

Keywords： ferrocement     moment capacity     self-evolving neural network    

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on the credit classification of practicing qualification personnel in construction market based on self-organizingneural network

Fang Zhiqing,Wang Xueqing,Li Baolong

Strategic Study of CAE 2011, Volume 13, Issue 9,   Pages 105-108

Abstract: characters of the practicing qualification personnel in construction market, evaluation method based on the self-organizingnerural network is brought out to analyze the credit classification of the practicing qualificationThen a self-organizing competitive neural network is built.

Keywords： practicing qualification personnel     credit     cluster analysis     self-organizing neural network    

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Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 2,   Pages 284-305 doi: 10.1007/s11709-022-0901-6

Abstract: Fiber-reinforced self-compacting concrete (FRSCC) is a typical construction material, and its compressiveArtificial neural network, random forest, and categorical gradient boosting (CatBoost) models were optimized

Keywords： compressive strength     self-compacting concrete     artificial neural network     decision tree     CatBoost    

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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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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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A hybrid machine learning model to estimate self-compacting concrete compressive strength

Hai-Bang LY; Thuy-Anh NGUYEN; Binh Thai PHAM; May Huu NGUYEN

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 8,   Pages 990-1002 doi: 10.1007/s11709-022-0864-7

Abstract: This study examined the feasibility of using the grey wolf optimizer (GWO) and artificial neural network(ANN) to predict the compressive strength (CS) of self-compacting concrete (SCC).

Keywords： artificial neural network     grey wolf optimize algorithm     compressive strength     self-compacting concrete    

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Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

Frontiers of Environmental Science & Engineering 2021, Volume 15, Issue 6, doi: 10.1007/s11783-021-1430-6

Abstract:

• UV-vis absorption analyzer was applied in drainage type online recognition.

Keywords： Drainage online recognition     UV-vis spectra     Derivative spectrum     Convolutional neural network    

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A neural network-based production process modeling and variable importance analysis approach in corn

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 3,   Pages 358-371 doi: 10.1007/s11705-022-2190-y

Abstract: In this paper, a neural network-based production process modeling and variable importance analysis approachnetwork/recurrent neural network based modeling and extended weights connection method.by the extended weight connection method, and 20 of the most important sites are selected for each neuralnetwork.The results indicate that the multilayer perceptron and recurrent neural network models have a relative

Keywords： big data     corn to sugar factory     neural network     variable importance analysis    

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Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 3, doi: 10.1007/s11465-022-0692-4

Abstract: under different pump health conditions are fused into RGB images and then recognized by a convolutional neuralnetwork.

Keywords： axial piston pump     fault diagnosis     convolutional neural network     multi-sensor data fusion    

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Machine learning and neural network supported state of health simulation and forecasting model for lithium-ion

Frontiers in Energy doi: 10.1007/s11708-023-0891-7

Abstract: branches of AI, to lithium-ion battery state of health (SOH), focusing on the advantages and strengths of neuralnetwork (NN) methods in ML for lithium-ion battery SOH simulation and prediction.

Keywords： machine learning     lithium-ion battery     state of health     neural network     artificial intelligence    

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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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PID neural network control of a membrane structure inflation system

Qiushuang LIU, Xiaoli XU

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 4,   Pages 418-422 doi: 10.1007/s11465-010-0117-7

Abstract: The neuron PID controller makes use of neuron self-learning ability, complies with certain optimum indicatorsResults show that the neural network PID controller can adapt to the changes in system structure parameters

Keywords： PID     neural network     membrane structure    

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and load sharing pattern of piled raft using nonlinear regression and LM algorithm-based artificial neuralnetwork

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 5,   Pages 1181-1198 doi: 10.1007/s11709-021-0744-6

Abstract: obtained results are then checked statistically with nonlinear multiple regression (NMR) and artificial neuralnetwork (ANN) modeling, and some prediction models are proposed.

Keywords： interaction     load sharing ratio     piled raft     nonlinear regression     artificial neural network    

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Title Author Date Type Operation

Estimating moment capacity of ferrocement members using self-evolving network

Abdussamad ISMAIL

Journal Article

on the credit classification of practicing qualification personnel in construction market based on self-organizingneural network

Fang Zhiqing,Wang Xueqing,Li Baolong

Journal Article

Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting

Journal Article

Multiscale computation on feedforward neural network and recurrent neural network

Bin LI, Xiaoying ZHUANG

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

A hybrid machine learning model to estimate self-compacting concrete compressive strength

Hai-Bang LY; Thuy-Anh NGUYEN; Binh Thai PHAM; May Huu NGUYEN

Journal Article

Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

Journal Article

A neural network-based production process modeling and variable importance analysis approach in corn

Journal Article

Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network

Journal Article

Machine learning and neural network supported state of health simulation and forecasting model for lithium-ion

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

PID neural network control of a membrane structure inflation system

Qiushuang LIU, Xiaoli XU

Journal Article

and load sharing pattern of piled raft using nonlinear regression and LM algorithm-based artificial neuralnetwork

Journal Article