Article
Computer Science, Theory & Methods
Sharanjit Kaur, Ayushi Gupta, Rakhi Saxena
Summary: The issue of identifying key players or important nodes in complex network analysis is addressed through the introduction of a new centrality measure called Affinity Centrality, which leverages both weighted in-degrees and out-degrees of nodes to evaluate their importance. Experimental results on real-world networks demonstrate that this centrality measure can rank nodes more accurately compared to other established measures.
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2021)
Article
Physics, Multidisciplinary
Yin-Ting Zhang, Wei-Xing Zhou
Summary: The study constructed four international crop trade networks using trade datasets of major crops, revealing increasing globalization in international crop trade and different trade patterns in different networks. The analysis showed that node degrees do not follow power laws, while link weights do. It also found a positive correlation between in-degree and out-degree, and a negative correlation between in-degree and clustering coefficient. Each network exhibited a unique topology different from the whole food network, providing valuable insights into specific crop trades.
Article
Engineering, Electrical & Electronic
Shijie Ren, Feng Zhou
Summary: This article proposes a multiscale evolving weighted graph convolutional network for PolSAR image classification, demonstrating superior performance and generalization capacity.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Physics, Multidisciplinary
U. Pigorsch, M. Sabek
Summary: This paper examines assortative mixing in weighted networks, introduces a generalisation of assortativity concept, provides procedures for assessing and interpreting assortativity, and demonstrates its usefulness in analysing real-world networks.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Volodymyr Melnykov, Shuchismita Sarkar, Yana Melnykov
Summary: This paper introduces a novel approach based on mixture models for modeling and clustering directed weighted networks, with computational issues effectively addressed using MCMC techniques. The utility of the method is demonstrated through experiments and applications to real-life data on export trade amounts for European countries.
PATTERN RECOGNITION
(2021)
Article
Mathematics
Athul Shibu, Dong-Gyu Lee
Summary: Convolutional neural networks have shown good performance in computer vision tasks. However, the hand-crafted network configurations lead to inefficiency. The proposed EvolveNet algorithm is a task-agnostic evolutionary search algorithm that can automatically find the optimal network structure. Experiments demonstrate the superiority of this method.
Article
Operations Research & Management Science
Cecile Bastidon, Antoine Parent
Summary: This article examines the application of operations research methods on network graphs in financial cliometrics. The results demonstrate the broad field of application for these methods. Through analyzing the evolution of the global stock market network and its impact on system resilience, the study highlights the role of network structure and path dependence in financial history.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Tianlong Fan, Hao Li, Xiao-Long Ren, Shuqi Xu, Youzhao Gou, Linyuan Lu
Summary: By analyzing global trade network data, we can identify the importance of countries and regions in this network and track their significance over time. The economic scale of a country has a strong impact on its position in the trade network.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2021)
Article
Computer Science, Artificial Intelligence
Xin Luo, Hao Wu, Zhi Wang, Jianjun Wang, Deyu Meng
Summary: This study proposes a novel and efficient approach to represent large-scale dynamically weighted directed networks (DWDNs), which can extract rich knowledge from incomplete DWDNs.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Oceanography
M. A. Dorantes-Gonzalez, J. M. Hernandez-Gueria, F. Arreguin-Sanchez
Summary: In this study, the influence of commercial network relationships on economic performance and profit distribution in the shark market in Mexico was investigated. Interviews were conducted with fishermen, permit holders, and traders in local, regional, and main markets for shark products. A weighted network of the shark market was built using the obtained information, and centrality indices and monetary contribution of each actor were calculated. The findings indicate that shark fin exporters have the highest net unitary profits, while traders of shark meat and fillet have the highest net profits. The organization of actors, quantity traded, out-degree, and out-closeness were identified as factors positively affecting the economic performance of the shark market.
OCEAN & COASTAL MANAGEMENT
(2023)
Article
Physics, Multidisciplinary
Xiaochen Pi, Longkun Tang, Xiangzhong Chen
Summary: This paper introduces a strength-based directed weighted scale-free network model, and through theoretical analysis and simulations, it demonstrates the network characteristics and discusses the relationship between the power-law exponent and parameters.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Katarina Kostelic, Marko Turk
Summary: The application of social network analysis in the world tourism network is limited and needs a research update. This research aims to examine the topology of the world tourism network in 2018 and discuss its significance. The data analysis provides insight into the network structure and characteristics, but only scratches the surface of potential for further research.
APPLIED SCIENCES-BASEL
(2021)
Article
Automation & Control Systems
Long Sun, Zhenbing Liu, Xiyan Sun, Licheng Liu, Rushi Lan, Xiaonan Luo
Summary: In this paper, a fast and lightweight framework named weighted multi-scale residual network (WMRN) is proposed for a better tradeoff between image super-resolution performance and computational efficiency. The network utilizes depthwise separable convolutions and weighted multi-scale residual blocks to improve efficiency and multi-scale representation capability, with Convolutional layers in the reconstruction subnetwork to filter feature maps for high-quality image reconstruction. Extensive experiments show the effectiveness of WMRN compared to several state-of-the-art algorithms.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
Article
Engineering, Environmental
Hakan Tongal, Bellie Sivakumar
Summary: The study applies transfer entropy concept to analyze rainfall dynamics in a complex network, finding high in- and out-clustering values in the northern regions, indicating mutual influence among nodes. Conversely, nodes in Western Australia and Victoria have lower clustering values but significant impact on other nodes.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2022)
Article
Green & Sustainable Science & Technology
Ping Tu, Qianqian Zhou, Meng Qi
Summary: This study introduced the complex network theory to simulate the topographic spatial structure and topological relationship of erosion areas. By constructing directed weighted complex networks and combining existing erosion evaluation factors, the random forest model was used to identify soil erosion types and risks in the Chinese Loess Plateau. Results showed that combining complex network factors with existing evaluation factors improved the identification performance of soil erosion.
Article
Automation & Control Systems
Xiaoling Wang, Housheng Su, Fan Zhang, Guanrong Chen
Summary: This article investigates the state estimation problem of a continuous-time linear time-invariant system in the presence of unknown external disturbance and measurement noise. A robust distributed interval observer is designed, which consists of a group of sensors communicating through a directed graph. The communication, heterogeneity, and undetectability of the sensors impose stringent requirements on the observer construction. To address these restrictions, an internally positive representation from a single agent system is introduced. Numerical simulations are conducted to validate the theoretical results.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Xu Zhang, Guanrong Chen
Summary: A new geometric criterion is developed to determine the existence of chaos in continuous-time autonomous systems in three-dimensional Euclidean spaces. This criterion differs from traditional methods as it does not rely on equilibrium points or the condition of transversal homoclinic or heteroclinic orbit of a Poincare map.
JOURNAL OF DYNAMICAL AND CONTROL SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Qiang Lai, Zhiqiang Wan, Hui Zhang, Guanrong Chen
Summary: This article presents a design of a new Hopfield neural network that can generate multiscroll attractors by utilizing a new memristor as a synapse in the network. The memristor is constructed with hyperbolic tangent functions and its parameters can effectively control the number of double scrolls in an attractor. Numerical analysis reveals amplitude control effects and quantitatively controllable multistability. Furthermore, a novel image encryption scheme based on the proposed memristive neural network is designed and evaluated, demonstrating good encryption performances.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Mingzhe Zhu, Wanyue Xu, Zhongzhi Zhang, Haibin Kan, Guanrong Chen
Summary: In this paper, the resistance distances in networks with higher order interactions are studied, and exact formulas for various quantities related to resistance distances are derived. The results show that the average resistance distance tends to a q-dependent constant.
Article
Automation & Control Systems
Guanghui Wen, Peijun Wang, Yuezu Lv, Guanrong Chen, Jialing Zhou
Summary: This paper studies the problem of secure consensus for multiple-input-multiple-output (MIMO) linear multi-agent systems (MASs) under denial-of-service (DoS) attacks and proposes corresponding control schemes and conditions. By designing an unknown input observer and using multiple Lyapunov functions, it is shown that secure consensus can be achieved under certain threshold conditions.
ASIAN JOURNAL OF CONTROL
(2023)
Article
Automation & Control Systems
Yong Wang, Zhuo Liu, Leo Yu Zhang, Fabio Pareschi, Gianluca Setti, Guanrong Chen
Summary: This article performs a theoretical study on pseudorandom number generation using the well-studied 2-D coupled map lattice (2D CML). It proposes a method to extract uniformly distributed independent bits from the system orbits and demonstrates its effectiveness through simulation experiments.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Physics, Multidisciplinary
Jiashuo Sun, Linying Xiang, Guanrong Chen
Summary: In this article, the dynamical robustness of a directed complex network with additive noise is studied. The failure of a node in the network is modeled by injecting noise into the node. A new robustness metric is formulated to characterize the synchronization of the network to the additive noise under the framework of mean-square stochastic stability. It is found that the node dynamics plays a crucial role in the dynamical robustness of the directed network. Numerical simulations are provided for illustration and verification.
FRONTIERS IN PHYSICS
(2023)
Article
Automation & Control Systems
Mengfei Niu, Guanghui Wen, Yuezu Lv, Guanrong Chen
Summary: This paper presents a new design of an innovation-based stealthy attack strategy against distributed state estimation over a sensor network. The optimal distributed MMSE estimator is developed by fusing interaction measurements from neighboring nodes in the absence of network attack. The tradeoff between attack stealthiness and attack effects is determined by proposing a stealthy attack framework embedded with an adjustable parameter.
Article
Automation & Control Systems
Jie-Ning Wu, Xiang Li, Guanrong Chen
Summary: This article examines the controllability of multi-input/multi-output linear time-invariant systems in a snapback interlayer coupling framework. It establishes necessary and sufficient conditions for the controllability of three-layer snapback networks and obtains controllability conditions for the superposition of these networks. These conditions are related to smaller scale factor networks and illustrate the impact of interlayer coupling frameworks, intralayer network topologies, node dynamics, inner interactions, and external control inputs on the controllability of snapback networks. The controllability conditions of three-layer snapback networks are also extended to the M-layer setting. Several examples are provided to illustrate the effectiveness of these controllability conditions.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2023)
Article
Mathematics
Jiali Wang, Changbing Tang, Jianquan Lu, Guanrong Chen
Summary: In this paper, a decision optimization method based on zero-determinant (ZD) strategies is proposed to help workers in a crowdsourcing system make optimal decisions under incomplete information. The problem is formulated as an iterated game with incomplete information, and the optimal decision of workers in terms of ZD strategies is analyzed. Numerical simulations are conducted to demonstrate the performances of different strategies and the impact of parameters on the payoffs of workers.
Article
Automation & Control Systems
Wenbo Hu, Fei Chen, Linying Xiang, Guanrong Chen
Summary: This article studies coordinated tracking of underactuated and uncertain autonomous surface vehicles (ASVs) via model-reference reinforcement learning control. It is demonstrated that the proposed algorithm has a better performance over baseline control and effectively improves the training efficiency over reinforcement learning.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Zhen Liu, Liangguang Pan, Guanrong Chen
Summary: In this article, a computational model called link-information augmented twin autoencoders is proposed to remove noisy links from observed network and recover the real network. Extensive experiments show that the proposed model outperforms other methods in network denoising and provides interpretable evidence to support its superiority.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Mathematics, Interdisciplinary Applications
Yuqian Zhou, Guanrong Chen, Jibin Li
Summary: By applying the techniques from dynamical systems and singular traveling wave theory developed by Li and Chen [2007] to analyze the traveling wave system of the cubic Camassa-Holm type equation, it has been discovered that the bifurcation portraits of this equation exhibit all possible exact explicit bounded solutions (solitary wave solutions, periodic wave solutions, peakon as well as periodic peakons) under different parameter conditions. A total of 19 explicit exact parametric representations of the traveling wave system of the Camassa-Holm type equation are provided.
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
(2023)
Article
Computer Science, Artificial Intelligence
Jiajun Zhou, Zhi Chen, Min Du, Lihong Chen, Shanqing Yu, Guanrong Chen, Qi Xuan
Summary: In this paper, robust community detection methods are proposed to improve the performance and robustness of community detection for real-world networks. By enhancing network structure through two generic algorithms, significant performance improvement is achieved for representative community detection algorithms. Additionally, the new methods also optimize the network structure and enhance robustness against adversarial attack.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Mathematics, Applied
Zhensu Wen, Guanrong Chen
Summary: This paper uses the methodology of dynamical systems and singular traveling wave theory to prove the existence of all possible bounded solutions of the traveling wave system in the Hertz chain model under different parameter conditions. Furthermore, it obtains 23 exact explicit parametric representations for various types of traveling wave systems.
DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES S
(2023)
Article
Mathematics, Applied
Melanie Kobras, Valerio Lucarini, Maarten H. P. Ambaum
Summary: In this study, a minimal dynamical system derived from the classical Phillips two-level model is introduced to investigate the interaction between eddies and mean flow. The study finds that the horizontal shape of the eddies can lead to three distinct dynamical regimes, and these regimes undergo transitions depending on the intensity of external baroclinic forcing. Additionally, the study provides insights into the continuous or discontinuous transitions of atmospheric properties between different regimes.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Shu-hong Xue, Yun-yun Yang, Biao Feng, Hai-long Yu, Li Wang
Summary: This research focuses on the robustness of multiplex networks and proposes a new index to measure their stability under malicious attacks. The effectiveness of this method is verified in real multiplex networks.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Julien Nespoulous, Guillaume Perrin, Christine Funfschilling, Christian Soize
Summary: This paper focuses on optimizing driver commands to limit energy consumption of trains under punctuality and security constraints. A four-step approach is proposed, involving simplified modeling, parameter identification, reformulation of the optimization problem, and using evolutionary algorithms. The challenge lies in integrating uncertainties into the optimization problem.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Alain Bourdier, Jean-Claude Diels, Hassen Ghalila, Olivier Delage
Summary: In this article, the influence of a turbulent atmosphere on the growth of modulational instability, which is the cause of multiple filamentation, is studied. It is found that considering the stochastic behavior of the refractive index leads to a decrease in the growth rate of this instability. Good qualitative agreement between analytical and numerical results is obtained.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Ling An, Liming Ling, Xiaoen Zhang
Summary: In this paper, an integrable fractional derivative nonlinear Schrodinger equation is proposed and a reconstruction formula of the solution is obtained by constructing an appropriate Riemann-Hilbert problem. The explicit fractional N-soliton solution and the rigorous verification of the fractional one-soliton solution are presented.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Marzia Bisi, Nadia Loy
Summary: This paper proposes and investigates general kinetic models with transition probabilities that can describe the simultaneous change of multiple microscopic states of the interacting agents. The mathematical properties of the kinetic model are proved, and the quasi-invariant asymptotic regime is studied and compared with other models. Numerical tests are performed to demonstrate the time evolution of distribution functions and macroscopic fields.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Carlos A. Pires, David Docquier, Stephane Vannitsem
Summary: This study presents a general theory for computing information transfers in nonlinear stochastic systems driven by deterministic forcings and additive and/or multiplicative noises. It extends the Liang-Kleeman framework of causality inference to nonlinear cases based on information transfer across system variables. The study introduces an effective method called the 'Causal Sensitivity Method' (CSM) for computing the rates of Shannon entropy transfer between selected causal and consequential variables. The CSM method is robust, cheaper, and less data-demanding than traditional methods, and it opens new perspectives on real-world applications.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Feiting Fan, Minzhi Wei
Summary: This paper focuses on the existence of periodic and solitary waves for a quintic Benjamin-Bona-Mahony (BBM) equation with distributed delay and diffused perturbation. By transforming the corresponding traveling wave equation into a three-dimensional dynamical system and applying geometric singular perturbation theory, the existence of periodic and solitary waves are established. The uniqueness of periodic waves and the monotonicity of wave speed are also analyzed.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Wangbo Luo, Yanxiang Zhao
Summary: We propose a generalized Ohta-Kawasaki model to study the nonlocal effect on pattern formation in binary systems with long-range interactions. In the 1D case, the model displays similar bubble patterns as the standard model, but Fourier analysis reveals that the optimal number of bubbles for the generalized model may have an upper bound.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Corentin Correia, Ana Cristina Moreira Freitas, Jorge Milhazes Freitas
Summary: The emergence of clustering of rare events is due to periodicity, where fast returns to target sets lead to a bulk of high observations. In this research, we explore the potential of a new mechanism to create clustering of rare events by linking observable functions to a finite number of points belonging to the same orbit. We show that with the right choice of system and observable, any given cluster size distribution can be obtained.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Enyu Fan, Changpin Li
Summary: This paper numerically studies the Allen-Cahn equations with different kinds of time fractional derivatives and investigates the influences of time derivatives on the solutions of the considered models.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Yuhang Zhu, Yinghao Zhao, Chaolin Song, Zeyu Wang
Summary: In this study, a novel approach called Time-Variant Reliability Updating (TVRU) is proposed, which integrates Kriging-based time-dependent reliability with parallel learning. This method enhances risk assessment in complex systems, showcasing exceptional efficiency and accuracy.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Chiara Cecilia Maiocchi, Valerio Lucarini, Andrey Gritsun, Yuzuru Sato
Summary: The predictability of weather and climate is influenced by the state-dependent nature of atmospheric systems. The presence of special atmospheric states, such as blockings, is associated with anomalous instability. Chaotic systems, like the attractor of the Lorenz '96 model, exhibit heterogeneity in their dynamical properties, including the number of unstable dimensions. The variability of unstable dimensions is linked to the presence of finite-time Lyapunov exponents that fluctuate around zero. These findings have implications for understanding the structural stability and behavior modeling of high-dimensional chaotic systems.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Christian Klein, Goksu Oruc
Summary: A numerical study on the fractional Camassa-Holm equations is conducted to construct smooth solitary waves and investigate their stability. The long-time behavior of solutions for general localized initial data from the Schwartz class of rapidly decreasing functions is also studied. Additionally, the appearance of dispersive shock waves is explored.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
Article
Mathematics, Applied
Vasily E. Tarasov
Summary: This paper extends the standard action principle and the first Noether theorem to consider the general form of nonlocality in time and describes dissipative and non-Lagrangian nonlinear systems. The general fractional calculus is used to handle a wide class of nonlocalities in time compared to the usual fractional calculus. The nonlocality is described by a pair of operator kernels belonging to the Luchko set. The non-holonomic variation equations of the Sedov type are used to describe the motion equations of a wide class of dissipative and non-Lagrangian systems. Additionally, the equations of motion are considered not only with general fractional derivatives but also with general fractional integrals. An application example is presented.
PHYSICA D-NONLINEAR PHENOMENA
(2024)
