Resource Type

Journal Article 183

Conference Videos 3

Conference Information 2

Year

2023 20

2022 27

2021 16

2020 25

2019 16

2018 12

2017 11

2016 17

2015 8

2014 3

2013 2

2012 1

2010 2

2009 2

2008 4

2007 6

2006 2

2005 3

2004 2

2003 1

open ︾

Keywords

neural networks 7

Deep learning 4

Artificial intelligence 3

Boolean control networks 3

Artificial neural networks 2

Boolean networks 2

Cognitive radio networks 2

Complex networks 2

Consensus 2

Convolutional neural networks (CNNs) 2

Deep neural networks 2

Deep reinforcement learning 2

Energy consumption 2

Fault diagnosis 2

OpenFlow 2

RBF neural networks 2

Semi-tensor product 2

artificial neural networks 2

learning algorithm 2

open ︾

Search scope:

排序： Display mode:

A PDEM-based perspective to engineering reliability: From structures to lifeline networks

Jie LI

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 5,   Pages 1056-1065 doi: 10.1007/s11709-020-0636-1

Abstract: Research of reliability of engineering structures has experienced a developing history for more than 90 years. However, the problem of how to resolve the global reliability of structural systems still remains open, especially the problem of the combinatorial explosion and the challenge of correlation between failure modes. Benefiting from the research of probability density evolution theory in recent years, the physics-based system reliability researches open a new way for bypassing this dilemma. The present paper introduces the theoretical foundation of probability density evolution method in view of a broad background, whereby a probability density evolution equation for probability dissipative system is deduced. In conjunction of physical equations and structural failure criteria, a general engineering reliability analysis frame is then presented. For illustrative purposes, several cases are studied which prove the value of the proposed engineering reliability analysis method.

Keywords： PDEM     reliability     structure     lifeline networks    

HTML PDF Collect

Progress in lifeline engineering researches

LI Jie

Frontiers of Structural and Civil Engineering 2007, Volume 1, Issue 1,   Pages 34-40 doi: 10.1007/s11709-007-0003-5

Abstract: In this paper, an overview is given on several key issues and related research progress made in lifelineevolution analysis for nonlinear structural responses, and seismic reliability analysis of large-scale lifelinenetworks.Recommendations are given for further development of the lifeline engineering research.

Keywords： development     comparison     evolution analysis     nonlinear structural     large-scale    

HTML PDF Collect

Research on Operations Management Based on the Internet of Things and BIM of Urban Lifeline

Chen Xinghai,Ding Lieyun

Strategic Study of CAE 2014, Volume 16, Issue 10,   Pages 89-93

Abstract:

Frequent occurrences of safety accident in urban lifeline engineeringAccording to the current situation of security operations management in urban lifeline engineering, thepaper analyses the problems existing in the operational phase of urban lifeline, and discusses the adaptabilitycharacters, and puts forward a systemSframeworkSfor the securitySoperationsSmanagement center of urban lifeline

Keywords： Internet     of Things(IOT)     Building     Information Modeling(BIM)     Urban     Lifeline Engineering     Operations Management    

HTML PDF Collect

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 application. We propose a general mathematical framework, which couples the complex structure of the system with the nonlinear activation function to explore the decoupled dimension reduction method of high-dimensional system and reveal the calculation mechanism of the neural network. We apply our framework to some network models and a real system of the whole neuron map of Caenorhabditis elegans. Result shows that a simple linear mapping relationship exists between network structure and network behavior in the neural network with high-dimensional and nonlinear characteristics. Our simulation and theoretical results fully demonstrate this interesting phenomenon. Our new interpretation mechanism provides not only the potential mathematical calculation principle of neural network but also an effective way to accurately match and predict human brain or animal activities, which can further expand and enrich the interpretable mechanism of artificial neural network in the future.

Keywords： neural networks     interpretability     dynamical behavior     network decouple    

HTML PDF Collect

Capacity analysis for cognitive heterogeneous networks with ideal/non-ideal sensing

Tao HUANG, Ying-lei TENG, Meng-ting LIU, Jiang LIU

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 1,   Pages 1-11 doi: 10.1631/FITEE.1400129

Abstract: to irregular deployment of small base stations (SBSs), the interference in cognitive heterogeneous networks

Keywords： Cognitive heterogeneous networks     Markov chain     Stochastic geometry     Homogeneous Poisson point process (    

HTML PDF Collect

Study and Application of Steady Flow and Unsteady Flow Mathematical Model for Canal Networks

Zhang Mingliang,Shen Yongming

Strategic Study of CAE 2007, Volume 9, Issue 8,   Pages 92-96

Abstract: and canal networks is developed and the key issues on the model are expatiated particularly in this This model is applied to simulating the tree-type irrigation canal networks and complex loopedcanal networks.and river networks.and canal networks.

Keywords： Preissmann implicit scheme     canal networks and river networks     discharge distribution     water quality    

HTML PDF Collect

Evaluation of the situational awareness effects for smart distribution networks under the novel

Leijiao GE, Yuanliang LI, Suxuan LI, Jiebei ZHU, Jun YAN

Frontiers in Energy 2021, Volume 15, Issue 1,   Pages 143-158 doi: 10.1007/s11708-020-0703-2

Abstract: As a key application of smart grid technologies, the smart distribution network (SDN) is expected to have a high diversity of equipment and complexity of operation patterns. Situational awareness (SA), which aims to provide a critical visibility of the SDN, will enable a significant assurance for stable SDN operations. However, the lack of systematic evaluation through the three stages of perception, comprehensive, and prediction may prevent the SA technique from effectively achieving the performance necessary to monitor and respond to events in SDN. To analyze the feasibility and effectiveness of the SA technique for the SDN, a comprehensive evaluation framework with specific performance indicators and systematic weighting methods is proposed in this paper. Besides, to implement the indicator framework while addressing the key issues of human expert scoring ambiguity and the lack of data in specific SDN areas, an improved interval-based analytic hierarchy process-based subjective weighting and a multi-objective programming method-based objective weighting are developed to evaluate the SDN SA performance. In addition, a case study in a real distribution network of Tianjin China is conducted whose outcomes verify the practicality and effectiveness of the proposed SA technique for SDN operating security.

Keywords： distribution networks     operation and maintenance     expert systems    

HTML PDF Collect

Predicting the yield of pomegranate oil from supercritical extraction using artificial neural networks

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: The performance of these networks was evaluated using the coefficient of determination ( ) and the mean

Keywords： oil recovery     artificial intelligence     extraction     neural networks     supercritical extraction    

HTML PDF Collect

The use of Artificial Neural Networks to estimate seismic damage and derive vulnerability functions for

Tiago Miguel FERREIRA, João ESTÊVÃO, Rui MAIO, Romeu VICENTE

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 3,   Pages 609-622 doi: 10.1007/s11709-020-0623-6

Abstract: obtained resorting to a classic damage formulation and an innovative approach based on Artificial Neural Networks

Keywords： Artificial Neural Networks     seismic vulnerability     masonry buildings     damage estimation     vulnerability curves    

HTML PDF Collect

Exploring self-organization and self-adaption for smart manufacturing complex networks

Frontiers of Engineering Management 2023, Volume 10, Issue 2,   Pages 206-222 doi: 10.1007/s42524-022-0225-1

Abstract: Specifically, a general model of smart manufacturing complex networks is constructed using scale-freenetworks to interconnect heterogeneous manufacturing resources represented by network vertices at multipleinto virtual manufacturing services using cloud technology, which can be added to or removed from the networksMaterials, information, and financial assets are passed through interactive links across the networks

Keywords： cyber–physical systems     Industrial Internet of Things     smart manufacturing complex networks     self-organization    

HTML PDF Collect

An overview of the reliability metrics for power grids and telecommunication networks

Frontiers of Engineering Management 2021, Volume 8, Issue 4,   Pages 531-544 doi: 10.1007/s42524-021-0167-z

Abstract: Power grids deliver energy, and telecommunication networks transmit information.comprehensive overview of the development of reliability metrics for power grids and telecommunication networks

Keywords： reliability     metrics     power grids     telecommunication networks    

HTML PDF Collect

Aslotted floor acquisitionmultiple access based MACprotocol for underwater acoustic networks withRTS

Liang-fang QIAN,Sen-lin ZHANG,Mei-qin LIU

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 3,   Pages 217-226 doi: 10.1631/FITEE.1400187

Abstract: error rate pose great challenges in media access control (MAC) protocol design for underwater acoustic networksprotocol called slotted floor acquisition multiple access (slotted-FAMA) suitable for underwater acoustic networksHowever, slotted-FAMA is not suitable for dense networks since the multiple request-to-send (RTS) attemptsproblem in dense networks is serious and greatly limits the network throughput.overcome this drawback, this paper proposes a slotted-FAMA based MAC protocol for underwater acoustic networks

Keywords： Underwater acoustic networks     Medium access control (MAC)     Request-to-send (RTS) competition     Throughput    

HTML PDF Collect

METABOLIC AND TRANSCRIPTOME ANALYSIS REVEALS METABOLITE VARIATION AND FLAVONOID REGULATORY NETWORKS IN

Frontiers of Agricultural Science and Engineering 2021, Volume 8, Issue 2,

Abstract:

Metabolites, especially secondary metabolites, are very important in the adaption of tea plants and the quality of tea products. Here, we focus on the seasonal variation in metabolites of fresh tea shoots and their regulatory mechanism at the transcriptional level. The metabolic profiles of fresh tea shoots of 10 tea accessions collected in spring, summer, and autumn were analyzed using ultra-performance liquid chromatography coupled with quadrupole-obitrap mass spectrometry. We focused on the metabolites and key genes in the phenylpropanoid/flavonoid pathway integrated with transcriptome analysis. Multivariate statistical analysis indicates that metabolites were distinctly different with seasonal alternation. Flavonoids, amino acids, organic acids and alkaloids were the predominant metabolites. Levels of most key genes and downstream compounds in the flavonoid pathway were lowest in spring but the catechin quality index was highest in spring. The regulatory pathway was explored by constructing a metabolite correlation network and a weighted gene co-expression network.

 

HTML PDF Collect

Visualization of force networks in 2D dense granular materials

Jianguo LIU, Qicheng SUN, Feng JIN,

Frontiers of Structural and Civil Engineering 2010, Volume 4, Issue 1,   Pages 109-115 doi: 10.1007/s11709-010-0003-8

Abstract: Dense granular matter is a conglomeration of discrete solid and closely packed particles. As subjected to external loadings, the stress is largely transmitted by heavily stressed chains of particles forming a sparse network of larger contact forces. To understand the structure and evolution of force chains, a photoelastic technique was improved for determining stresses and strains in the assemblies of photoelastic granular disks in this paper. A two-dimensional vertical slab was designed. It contains 7200 polydispersed photoelastic disks and is subjected to a localized probe penetrating at the top of the slab to mimic the cone penetration test. The interparticle contact force distribution was found a peak around the mean value, a roughly exponential tail for greater force and a dip toward zero for smaller force. The force chain network around the probe tip was depicted, and the contact angle distribution of particles in force chains was found to be well aligned in the directions of major principal stress.

Keywords： granular matter     force chain     multiscale modeling    

HTML PDF Collect

Title Author Date Type Operation

A PDEM-based perspective to engineering reliability: From structures to lifeline networks

Jie LI

Journal Article

Progress in lifeline engineering researches

LI Jie

Journal Article

Research on Operations Management Based on the Internet of Things and BIM of Urban Lifeline

Chen Xinghai,Ding Lieyun

Journal Article

Novel interpretable mechanism of neural networks based on network decoupling method

Journal Article

Capacity analysis for cognitive heterogeneous networks with ideal/non-ideal sensing

Tao HUANG, Ying-lei TENG, Meng-ting LIU, Jiang LIU

Journal Article

Study and Application of Steady Flow and Unsteady Flow Mathematical Model for Canal Networks

Zhang Mingliang,Shen Yongming

Journal Article

Evaluation of the situational awareness effects for smart distribution networks under the novel

Leijiao GE, Yuanliang LI, Suxuan LI, Jiebei ZHU, Jun YAN

Journal Article

Predicting the yield of pomegranate oil from supercritical extraction using artificial neural networks

J. Sargolzaei, A. Hedayati Moghaddam

Journal Article

The use of Artificial Neural Networks to estimate seismic damage and derive vulnerability functions for

Tiago Miguel FERREIRA, João ESTÊVÃO, Rui MAIO, Romeu VICENTE

Journal Article

Dong Chaoyang: Interpretable Memristive-LSTM Networks for Probabilistic Power System Forecasting (2022

7 Jul 2022

Conference Videos

Exploring self-organization and self-adaption for smart manufacturing complex networks

Journal Article

An overview of the reliability metrics for power grids and telecommunication networks

Journal Article

Aslotted floor acquisitionmultiple access based MACprotocol for underwater acoustic networks withRTS

Liang-fang QIAN,Sen-lin ZHANG,Mei-qin LIU

Journal Article

METABOLIC AND TRANSCRIPTOME ANALYSIS REVEALS METABOLITE VARIATION AND FLAVONOID REGULATORY NETWORKS IN

Journal Article

Visualization of force networks in 2D dense granular materials

Jianguo LIU, Qicheng SUN, Feng JIN,

Journal Article