Dynamical analysis and near-optimal control strategy of a stochastic carbon emissions model [0.03%]
一种随机碳排放模型的动力学分析及近优化控制策略研究
Xinxin Wang,Tonghua Zhang,Sanling Yuan
Xinxin Wang
Mitigating carbon dioxide (CO2) emissions associated with energy generation is crucial for addressing the climate crisis. To better understand the dynamic relationship between CO2 concentration, human population, and energy consumption in a...
Bifurcation analysis of delay-coupling induced bistability in coupled van der Pol oscillators [0.03%]
延时耦合van der Pol振子诱导双稳态的分岔分析
Sergey Astakhov,Evgeny Elizarov,Galina Strelkova et al.
Sergey Astakhov et al.
It is shown that the coexistence of synchronous and asynchronous states, being typical for chimera states in large networks of coupled oscillators, can be formed in a minimal chain of two coupled van der Pol oscillators with dissipative del...
Serhiy Yanchuk,Erik Andreas Martens,Christian Kuehn et al.
Serhiy Yanchuk et al.
Adaptive dynamical networks (ADNs) describe systems in which the states of the network nodes and the network structure itself co-evolve over time. This interplay of two coupled dynamical processes underlies a wide range of natural and techn...
A novel approach for estimating largest Lyapunov exponents in one-dimensional chaotic time series using machine learning [0.03%]
基于机器学习的一维混沌时间序列最大李雅普诺夫指数估计的新方法
Andrei Velichko,Maksim Belyaev,Petr Boriskov
Andrei Velichko
Understanding and quantifying chaos from data remains challenging. We present a data-driven method for estimating the largest Lyapunov exponent (LLE) from one-dimensional chaotic time series using machine learning. A predictor is trained to...
Entropy production rate and time-reversibility for general jump diffusions on RRn [0.03%]
跳过程的熵产生率和时间反演性
Qi Zhang,Yubin Lu
Qi Zhang
This paper investigates the entropy production rate and time-reversibility for general jump diffusions (Lévy processes) on Rn. We first formulate the entropy production rate and explore its associated thermodynamic relations for jump diffu...
M Rosalie,S Mangiarotti
M Rosalie
The structure of the Lorenz-84 attractor is investigated in this study. Its dynamics belonging to weakly dissipative chaos, classical approaches cannot be used to analyze its structure. The color tracer mapping is introduced for this purpos...
Andrey V Andreev,Artem A Badarin,Dibakar Ghosh et al.
Andrey V Andreev et al.
In recent years, adaptive higher-order interactions have garnered significant attention. However, most studies on chimera states in higher-order interaction networks have not considered coupling adaptation. In this work, we study a network ...
Fractal geometry predicts dynamic differences in structural and functional connectomes [0.03%]
分形几何预测结构连接组和功能连接组的动态差异
Anca Rădulescu,Eva Kaslik,Alexandru Fikl et al.
Anca Rădulescu et al.
Understanding the intricate architecture of brain networks and its connection to brain function is essential for deciphering the underlying principles of cognition and disease. While traditional graph-theoretical measures have been widely u...
Collective directional switches of swarming systems with higher-order interactions [0.03%]
具有高阶相互作用的群集系统集体方向切换
Shijie Liu,Rui Xiao,Yongzheng Sun
Shijie Liu
Sudden coherent changes in the movement direction are common in animal groups; yet, the mechanism of higher-order and delayed interactions in shaping such collective switching dynamics remains poorly understood. Here, we propose a self-prop...
MEP-Net: Generating solutions to scientific problems with limited knowledge by maximum entropy principle [0.03%]
基于最大熵原理利用有限知识生成科学问题的解-MEP-Net
Wuyue Yang,Liangrong Peng,Guojie Li et al.
Wuyue Yang et al.
Maximum entropy principle (MEP) offers an effective and unbiased approach to inferring unknown probability distributions when faced with incomplete information, while neural networks provide the flexibility to learn complex distributions fr...