IF 2.7 2区数学

Chaos Pub Date : 2024-11-01 DOI: 10.1063/5.0222079

D Di Gangi, G Bormetti, F Lillo

引用次数: 0

Physics-informed line graph neural network for power flow calculation. 用于功率流计算的物理信息线图神经网络。

IF 2.7 2区数学

Chaos Pub Date : 2024-11-01 DOI: 10.1063/5.0235301

Hai-Feng Zhang, Xin-Long Lu, Xiao Ding, Xiao-Ming Zhang

{"title":"Physics-informed line graph neural network for power flow calculation.","authors":"Hai-Feng Zhang, Xin-Long Lu, Xiao Ding, Xiao-Ming Zhang","doi":"10.1063/5.0235301","DOIUrl":"https://doi.org/10.1063/5.0235301","url":null,"abstract":"Power flow calculation plays a significant role in the operation and planning of modern power systems. Traditional numerical calculation methods have good interpretability but high time complexity. They are unable to cope with increasing amounts of data in power systems; therefore, many machine learning based methods have been proposed for more efficient power flow calculation. Despite the good performance of these methods in terms of computation speed, they often overlook the importance of transmission lines and do not fully consider the physical mechanisms in the power systems, thereby weakening the prediction accuracy of power flow. Given the importance of the transmission lines as well as to comprehensively consider their mutual influence, we shift our focus from bus adjacency relationships to transmission line adjacency relationships and propose a physics-informed line graph neural network framework. This framework propagates information between buses and transmission lines by introducing the concepts of the incidence matrix and the line graph matrix. Based on the mechanics of the power flow equations, we further design a loss function by integrating physical information to ensure that the output results of the model satisfy the laws of physics and have better interpretability. Experimental results on different power grid datasets and different scenarios demonstrate the accuracy of our proposed model.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142603162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pulses in singularly perturbed reaction-diffusion systems with slowly mixed nonlinearity. 具有缓慢混合非线性的奇异扰动反应-扩散系统中的脉冲。

IF 2.7 2区数学

Chaos Pub Date : 2024-11-01 DOI: 10.1063/5.0228472

Yuanxian Chen, Yuhua Cai, Jianhe Shen

引用次数: 0

Vegetation restoration strategies in arid or semi-arid regions-From the perspective of optimal control. 干旱或半干旱地区的植被恢复战略--从优化控制的角度。

IF 2.7 2区数学

Chaos Pub Date : 2024-11-01 DOI: 10.1063/5.0206880

Li-Feng Hou, Shu-Peng Gao, Li-Li Chang, Yong-Ping Wu, Guo-Lin Feng, Zhen Wang, Gui-Quan Sun

引用次数: 0

An investigation of escape and scaling properties of a billiard system. 台球系统的逃逸和缩放特性研究。

IF 2.7 2区数学

Chaos Pub Date : 2024-11-01 DOI: 10.1063/5.0222215

Matheus Rolim Sales, Daniel Borin, Diogo Ricardo da Costa, José Danilo Szezech, Edson Denis Leonel

引用次数: 0

Symmetry breaker governs synchrony patterns in neuronal inspired networks. 对称性断路器制约着神经元启发网络的同步模式。

IF 2.7 2区数学

Chaos Pub Date : 2024-11-01 DOI: 10.1063/5.0209865

Anil Kumar, Edmilson Roque Dos Santos, Paul J Laurienti, Erik Bollt

{"title":"Symmetry breaker governs synchrony patterns in neuronal inspired networks.","authors":"Anil Kumar, Edmilson Roque Dos Santos, Paul J Laurienti, Erik Bollt","doi":"10.1063/5.0209865","DOIUrl":"10.1063/5.0209865","url":null,"abstract":"Experiments in the human brain reveal switching between different activity patterns and functional network organization over time. Recently, multilayer modeling has been employed across multiple neurobiological levels (from spiking networks to brain regions) to unveil novel insights into the emergence and time evolution of synchrony patterns. We consider two layers with the top layer directly coupled to the bottom layer. When isolated, the bottom layer would remain in a specific stable pattern. However, in the presence of the top layer, the network exhibits spatiotemporal switching. The top layer in combination with the inter-layer coupling acts as a symmetry breaker, governing the bottom layer and restricting the number of allowed symmetry-induced patterns. This structure allows us to demonstrate the existence and stability of pattern states on the bottom layer, but most remarkably, it enables a simple mechanism for switching between patterns based on the unique symmetry-breaking role of the governing layer. We demonstrate that the symmetry breaker prevents complete synchronization in the bottom layer, a situation that would not be desirable in a normal functioning brain. We illustrate our findings using two layers of Hindmarsh-Rose (HR) oscillators, employing the Master Stability function approach in small networks to investigate the switching between patterns.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142582402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mixed-mode oscillations and chaos in a complex chemical reaction network involving heterogeneous catalysis. 涉及异相催化的复杂化学反应网络中的混合模式振荡和混沌。

IF 2.7 2区数学

Chaos Pub Date : 2024-11-01 DOI: 10.1063/5.0231992

Hsing-Ya Li, Yu-Shu Chien, Ming-Shen Chiou

{"title":"Mixed-mode oscillations and chaos in a complex chemical reaction network involving heterogeneous catalysis.","authors":"Hsing-Ya Li, Yu-Shu Chien, Ming-Shen Chiou","doi":"10.1063/5.0231992","DOIUrl":"https://doi.org/10.1063/5.0231992","url":null,"abstract":"The nonlinear dynamical behavior in a complex isothermal reaction network involving heterogeneous catalysis is studied. The method first determines the multiple steady states in the reaction network. This is followed by an analysis of bifurcation continuations to identify several kinds of bifurcations, including limit point, Bogdanov-Takens, generalized Hopf, period doubling, and generalized period doubling. Numerical simulations are performed around the period doubling and generalized period doubling bifurcations. Rich nonlinear behaviors are observed, including simple sustained oscillations, mixed-mode oscillations, non-mixed-mode chaotic oscillations, and mixed-mode chaotic oscillations. Concentration-time plots, 2D phase portraits, Poincaré maps, maximum Lyapunov exponents, frequency spectra, and cascade of bifurcations are reported. Period-doubling and period-adding routes leading to chaos are observed. Maximum Lyapunov exponents are positive for all the chaotic cases, but they are also positive for some non-chaotic orbits. This result diminishes the reliability of using maximum Lyapunov exponents as a tool for determining chaos in the network under study.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142582401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Templex-based dynamical units for a taxonomy of chaos. 基于 Templex 的混沌分类动态单元。

IF 2.7 2区数学

Chaos Pub Date : 2024-11-01 DOI: 10.1063/5.0233160

Caterina Mosto, Gisela D Charó, Christophe Letellier, Denisse Sciamarella

引用次数: 0

Identifying influential nodes in social networks from the perspective of attack-defense game. 从攻防博弈的角度识别社交网络中具有影响力的节点。

IF 2.7 2区数学

Chaos Pub Date : 2024-11-01 DOI: 10.1063/5.0240052

Wen Hu, Ye Deng, Yu Xiao, Jun Wu

{"title":"Identifying influential nodes in social networks from the perspective of attack-defense game.","authors":"Wen Hu, Ye Deng, Yu Xiao, Jun Wu","doi":"10.1063/5.0240052","DOIUrl":"https://doi.org/10.1063/5.0240052","url":null,"abstract":"Influence spread analysis, a critical component of social network studies, focuses on the patterns and effects of information dissemination among interconnected entities. The core of influence spread analysis is to identify influential nodes that involve two distinct aspects: influence maximization (IM) and influence blocking maximization (IBM). However, when IM and IBM occur simultaneously, identifying influential nodes becomes an intricate decision-making challenge. This study addresses identifying influential nodes in social networks through an attack-defense game perspective, where an attacker maximizes influence and a defender minimizes it. We first develop a two-player static zero-sum game model considering resource constraints. Based on the equilibrium strategy of this game, we redefine the concept of influential nodes from various viewpoints. Extensive experiments on synthetic and real-world networks show that, in most cases, the defender preferentially defends critical nodes, while the attacker adopts the decentralized strategy. Only when resources are unevenly matched do both players tend to adopt centralized strategies. This study expands the connotation of influential nodes and provides a novel paradigm for the social network analysis with significant potential applications.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142557285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On the periodic behavior of the generalized Chazy differential equation. 论广义查兹微分方程的周期行为。

IF 2.7 2区数学

Chaos Pub Date : 2024-11-01 DOI: 10.1063/5.0209050

Ziwei Zhuang, Changjian Liu, Jiahui Luo

引用次数: 0

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