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Earthquakes in the north block of Tibet-Plateau and retrospect of prediction for Wenchuan M8.0 Earthquake

Men Kepei

Strategic Study of CAE 2009, Volume 11, Issue 6,   Pages 82-88

Abstract: The main orderly values are 53~54 a, 26~27 a, 11~12 a and 3~4 a.According to the information prediction theory of Weng Wenbo and self-organization network technologyearthquake prediction with Chinese characteristics, and conceive strong earthquake with magnitude 7 informationalnetwork structure.

Keywords： the north block of Tibet Plateau     informational orderly network structure     the great Wenchuan Earthquake    

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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 PID controller is used to control a nonlinear time-variant membrane structure inflation system.Results 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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Automated classification of civil structure defects based on convolutional neural network

Pierclaudio SAVINO, Francesco TONDOLO

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 305-317 doi: 10.1007/s11709-021-0725-9

Abstract: paper presents a method for automating concrete damage classification using a deep convolutional neural networkThe convolutional neural network was designed after an experimental investigation of a wide number ofTo increase the network robustness compared to images in real-world situations, different image configurationsmodel, with the highest validation accuracy of approximately 94%, was selected as the most suitable network

Keywords： concrete structure     infrastructures     visual inspection     convolutional neural network     artificial intelligence    

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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: In recent years, great attention has focused on the development of automated procedures for infrastructures control. Many efforts have aimed at greater speed and reliability compared to traditional methods of assessing structural conditions. The paper proposes a multi-level strategy, designed and implemented on the basis of periodic structural monitoring oriented to a cost- and time-efficient tunnel control plan. Such strategy leverages the high capacity of convolutional neural networks to identify and classify potential critical situations. In a supervised learning framework, Ground Penetrating Radar (GPR) profiles and the revealed structural phenomena have been used as input and output to train and test such networks. Image-based analysis and integrative investigations involving video-endoscopy, core drilling, jacking and pull-out testing have been exploited to define the structural conditions linked to GPR profiles and to create the database. The degree of detail and accuracy achieved in identifying a structural condition is high. As a result, this strategy appears of value to infrastructure managers who need to reduce the amount and invasiveness of testing, and thus also to reduce the time and costs associated with inspections made by highly specialized technicians.

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

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Machine learning-based seismic assessment of framed structures with soil-structure interaction

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 2,   Pages 205-223 doi: 10.1007/s11709-022-0909-y

Abstract: technique (MLT) to predict the seismic performance of low- to mid-rise frame structures considering soil-structureThe proposed framework is novel because it enables the designer to seismically assess the structure,

Keywords： seismic hazard     artificial neural network     soil-structure interaction     seismic analysis    

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Innovative Development Strategy of New Network Technologies

Li Dan, Hu Yuxiang, Wu Jiangxing

Strategic Study of CAE 2021, Volume 23, Issue 2,   Pages 15-21 doi: 10.15302/J-SSCAE-2021.02.003

Abstract: for new businesses and the continuous development of the Internet economy have increasingly demanded networkstatus of new network fields in China and abroad, and summarize the development trend of new networkSubsequently, we summarize the gaps and development goals of China in the new network field.Finally we propose the key technologies for the new network development in China, including new network, network intelligence technology, and endogenous security structure.

Keywords： new network architecture，full-dimension definable，polymorphic addressing and routing，network intelligence， endogenous security structure    

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Sustainability performance analysis of environment innovation systems using a two-stage network DEA model

Frontiers of Engineering Management   Pages 425-438 doi: 10.1007/s42524-022-0205-5

Abstract: The term environmental innovation system refers to an innovation network composed of enterprises, universitiessystem performance constantly assume a single-stage independent system while ignoring its internal structure

Keywords： envelopment analysis     environmental efficiency     environmental innovation system     shared resources     two-stage structure    

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Orderly decorated nanostructural photoelectrodes with uniform spherical TiO

A. M. Bakhshayesh,S. S. Azadfar

Frontiers of Chemical Science and Engineering 2015, Volume 9, Issue 4,   Pages 532-540 doi: 10.1007/s11705-015-1549-8

Abstract: This study presents a novel nanostructural electrode made of 20-nm-diameter nanoparticles, which orderly

Keywords： dye-sensitized solar cell     uniform particles     TiO2 gel process     light harvesting    

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Dynamic aspects of domination networks Personal View

Yu-xian LIU, Ronald ROUSSEAU

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 4,   Pages 635-648 doi: 10.1631/FITEE.1800553

Abstract: The changes in the graph resulting from network dynamics are studied.As such, we provide examples of a dominance structure in a directed, acyclic network.We calculate the change in the D-measure, which is a measure expressing the degree of dominance in a networkwhen nodes are added to an existing simple network.

Keywords： Domination     Power structure     Digraphs     Network dynamics    

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Damage assessment and diagnosis of hydraulic concrete structures using optimization-based machine learning technology

Frontiers of Structural and Civil Engineering   Pages 1281-1294 doi: 10.1007/s11709-023-0975-9

Abstract: Changes in the concrete structure will result in changes in parameters such as the frequency mode andmethod for concrete structures is established using an artificial bee colony backpropagation neural network

Keywords： hydraulic structure     curvature mode     damage detection     artifical neural network     artificial bee colony    

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A new item-based deep network structure using a restricted Boltzmann machine for collaborative filtering Article

Yong-ping DU, Chang-qing YAO, Shu-hua HUO, Jing-xuan LIU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 5,   Pages 658-666 doi: 10.1631/FITEE.1601732

Abstract: a new item-based restricted Boltzmann machine (RBM) approach for CF and use the deep multilayer RBM networkstructure, which alleviates the data sparsity problem and has excellent ability to extract features.The parameters are learned layer by layer in the deep network.The new feature vector discovered by the multilayer RBM network structure is very effective in predicting

Keywords： Restricted Boltzmann machine     Deep network structure     Collaborative filtering     Recommendation system    

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Output feedback stabilizer design of Boolean networks based on network structure Research Articles

Jie ZHONG, Bo-wen LI, Yang LIU, Wei-hua GUI

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 247-259 doi: 10.1631/FITEE.1900229

Abstract: Based on network structure information describing coupling connections among nodes, an output feedbackFinally, a signal transduction network and a D. melanogaster segmentation polarity gene network are presented

Keywords： Boolean networks     Output feedback stabilizer     Network structure     Semi-tensor product of matrices    

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Influence of pore structure on biologically activated carbon performance and biofilm microbial characteristics

Frontiers of Environmental Science & Engineering 2021, Volume 15, Issue 6, doi: 10.1007/s11783-021-1419-1

Abstract:

• Pore structure affects biologically activated carbon performance.

Keywords： Granular activated carbon     Biologically activated carbon filter     Bacterial community structure     Porestructure    

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Hierarchical fractal structure of perfect single-layer graphene

T. Zhang, K. Ding

Frontiers of Mechanical Engineering 2013, Volume 8, Issue 4,   Pages 371-382 doi: 10.1007/s11465-013-0279-1

Abstract:

The atomic lattice structure of perfect single-layer graphene that can actually be regarded as a kindof hierarchical fractal structure from the perspective of fractal geometry was studied for the firstThree novel and special discoveries on hierarchical fractal structure and sets were unveiled upon examinationThe interior fractal-type structure was discovered to be the fifth space-filling curve from physicalA fundamental example of a multi-fractal structure was also presented.

Keywords： hierarchical fractal structure     fractal dimension     the fifth space-filling curve     multi-fractal structure    

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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 applicationWe propose a general mathematical framework, which couples the complex structure of the system with theWe apply our framework to some network models and a real system of the whole neuron map of CaenorhabditisResult shows that a simple linear mapping relationship exists between network structure and network behaviorin the neural network with high-dimensional and nonlinear characteristics.

Keywords： neural networks     interpretability     dynamical behavior     network decouple    

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Title Author Date Type Operation

Earthquakes in the north block of Tibet-Plateau and retrospect of prediction for Wenchuan M8.0 Earthquake

Men Kepei

Journal Article

PID neural network control of a membrane structure inflation system

Qiushuang LIU, Xiaoli XU

Journal Article

Automated classification of civil structure defects based on convolutional neural network

Pierclaudio SAVINO, Francesco TONDOLO

Journal Article

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

Journal Article

Machine learning-based seismic assessment of framed structures with soil-structure interaction

Journal Article

Innovative Development Strategy of New Network Technologies

Li Dan, Hu Yuxiang, Wu Jiangxing

Journal Article

Sustainability performance analysis of environment innovation systems using a two-stage network DEA model

Journal Article

Orderly decorated nanostructural photoelectrodes with uniform spherical TiO

A. M. Bakhshayesh,S. S. Azadfar

Journal Article

Dynamic aspects of domination networks

Yu-xian LIU, Ronald ROUSSEAU

Journal Article

Damage assessment and diagnosis of hydraulic concrete structures using optimization-based machine learning technology

Journal Article

A new item-based deep network structure using a restricted Boltzmann machine for collaborative filtering

Yong-ping DU, Chang-qing YAO, Shu-hua HUO, Jing-xuan LIU

Journal Article

Output feedback stabilizer design of Boolean networks based on network structure

Jie ZHONG, Bo-wen LI, Yang LIU, Wei-hua GUI

Journal Article

Influence of pore structure on biologically activated carbon performance and biofilm microbial characteristics

Journal Article

Hierarchical fractal structure of perfect single-layer graphene

T. Zhang, K. Ding

Journal Article

Novel interpretable mechanism of neural networks based on network decoupling method

Journal Article