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Complete synchronization of coupled Boolean networks with arbitrary finite delays Research Articles

Jie LIU, Lulu LI, HabibM. FARDOUN

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 281-293 doi: 10.1631/FITEE.1900438

Abstract: In this study, the complete synchronization problem of coupled delayed Boolean networks (CDBNs) is investigatedThe state delays and output delays may not be equal, and the state delay in each Boolean network may

Keywords： Boolean networks     Synchronization     Time delay    

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Cascading decomposition of Boolean control networks: a graph-theoreticalmethod Research Articles

Yi-feng LI, Jian-dong ZHU

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 304-315 doi: 10.1631/FITEE.1900422

Abstract: Two types of cascading decomposition problems of Boolean control networks are investigated using a raph-theoretical

Keywords： Boolean control networks     Semi-tensor product     Cascading decomposition     Graphic condition    

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Controllability of Boolean control networks with multiple time delays in both states and controls Research Article

Yifeng LI, Lan WANG,liyifeng@cqnu.edu.cn,wanglan202212@126.com

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 6,   Pages 906-915 doi: 10.1631/FITEE.2200618

Abstract: In this paper, the problem of of (BCNs) with multiple s in both states and controls is investigated. First, the problem of BCNs with multiple s in controls is considered. For this problem, a matrix is constructed by defining a new product of matrices, based on which a necessary and sufficient condition is obtained. Then, the of BCNs with multiple s in states is studied by giving a necessary and sufficient condition. Subsequently, based on these results, a matrix for BCNs with multiple s in both states and controls is proposed that provides a concise condition. Finally, two examples are given to illustrate the main results.

Keywords： Boolean control networks     Semi-tensor product of matrices     Controllability     Time delay    

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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: In genetic regulatory networks, a stable configuration can represent the evolutionary behavior of cellWe present analytical investigations on output feedback stabilizer design of Boolean networks (BNs) to

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

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Optimal one-bit perturbation in Boolean networks based on cascading aggregation Research Articles

Jin-feng PAN, Min MENG

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 294-303 doi: 10.1631/FITEE.1900411

Abstract: BOAs) of desired attractors and minimizes the size of the BOAs of undesired attractors for large-scale Booleannetworks by cascading aggregation.

Keywords： Large-scale Boolean network     Attractor     Cascading aggregation     One-bit perturbation    

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Stability of Boolean networks with state-dependent random impulses

Ya-wen Shen, Yu-qian Guo, Wei-hua Gui,shenyawen@csu.edu.cn,gyuqian@csu.edu.cn,gwh@csu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 2,   Pages 141-286 doi: 10.1631/FITEE.1900454

Abstract: We investigate the stability of Boolean networks (BNs) with impulses triggered by both states and random

Keywords： Boolean network with impulses     Forward completeness     Finite-time stability with probability one     Asymptotical    

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Switching-based stabilization of aperiodic sampled-data Boolean control networks with all subsystems Research Articles

Liang-jie SUN, Jian-quan LU, Wai-Ki CHING

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 260-267 doi: 10.1631/FITEE.1900312

Abstract: We aim to further study the global stability of Boolean control networks (BCNs) under aperiodic sampleddataAccording to our previous work, it is known that a BCN under ASDC can be transformed into a switched Boolean

Keywords： Aperiodic sampled-data control     Boolean control networks     Unstable subsystem     Discretized Lyapunov function    

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An algorithm for identifying symmetric variables based on the order eigenvalue matrix Article

Xiao-hua LI, Ji-zhong SHEN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1644-1653 doi: 10.1631/FITEE.1601052

Abstract: To simplify the process for identifying 12 types of symmetric variables in Boolean functions, we propose12 types of symmetric variables, an algorithm is proposed for identifying symmetric variables of the BooleanThis algorithm can be applied to identify the symmetric variables of Boolean functions with or withoutis an optimal detection method in terms of the applicability of the number of logic variables, the Boolean

Keywords： Boolean function     Symmetric variable     Boolean logic algebra system     Order eigenvalue matrix     Truth table    

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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 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    

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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 (    

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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    

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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    

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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    

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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    

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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    

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Title Author Date Type Operation

Complete synchronization of coupled Boolean networks with arbitrary finite delays

Jie LIU, Lulu LI, HabibM. FARDOUN

Journal Article

Cascading decomposition of Boolean control networks: a graph-theoreticalmethod

Yi-feng LI, Jian-dong ZHU

Journal Article

Controllability of Boolean control networks with multiple time delays in both states and controls

Yifeng LI, Lan WANG,liyifeng@cqnu.edu.cn,wanglan202212@126.com

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

Optimal one-bit perturbation in Boolean networks based on cascading aggregation

Jin-feng PAN, Min MENG

Journal Article

Stability of Boolean networks with state-dependent random impulses

Ya-wen Shen, Yu-qian Guo, Wei-hua Gui,shenyawen@csu.edu.cn,gyuqian@csu.edu.cn,gwh@csu.edu.cn

Journal Article

Switching-based stabilization of aperiodic sampled-data Boolean control networks with all subsystems

Liang-jie SUN, Jian-quan LU, Wai-Ki CHING

Journal Article

An algorithm for identifying symmetric variables based on the order eigenvalue matrix

Xiao-hua LI, Ji-zhong SHEN

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

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

Journal Article