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A q-analogue for partial-fraction decomposition of a rational function and its application 有理函数偏分分解的 q 类比及其应用
Pub Date : 2024-06-12 DOI: 10.1186/s13662-024-03814-7
Ze-Qian Luo, Qiu-Ming Luo
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引用次数: 0
A pair of centro-symmetric heteroclinic orbits coined 一对中心对称的异质轨道被称为
Pub Date : 2024-05-22 DOI: 10.1186/s13662-024-03809-4
Haijun Wang, Jun Pan, Guiyao Ke, Feiyu Hu
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引用次数: 0
The impact of resource limitation on the pest-natural enemy ecosystem with anti-predator behavior and fear effect 资源限制对害虫-天敌生态系统的影响与反捕食行为和恐惧效应
Pub Date : 2024-04-24 DOI: 10.1186/s13662-024-03804-9
Wenjie Qin, Zhengjun Dong
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引用次数: 0
Conservative Fourier spectral method for a class of modified Zakharov system with high-order space fractional quantum correction 一类具有高阶空间分数量子校正的修正Zakharov系统的保守傅里叶谱方法
Pub Date : 2023-11-03 DOI: 10.1186/s13662-023-03790-4
Tao Guo, Aiguo Xiao, Junjie Wang, Xueyang Li
Abstract In this paper, we consider the Fourier spectral method and numerical investigation for a class of modified Zakharov system with high-order space fractional quantum correction. First, the numerical scheme of the system is developed with periodic boundary condition based on the Crank–Nicolson/leap-frog methods in time and the Fourier spectral method in space. Moreover, it is shown that the scheme preserves simultaneously mass and energy conservation laws. Second, we analyze stability and convergence of the numerical scheme. Last, the numerical experiments are given, and the results show the correctness of theoretical results and the efficiency of the conservative scheme.
本文研究了一类具有高阶空间分数阶量子校正的修正Zakharov系统的傅里叶谱方法和数值研究。首先,基于时间上的Crank-Nicolson /leap-frog方法和空间上的傅立叶谱方法,在周期边界条件下建立了系统的数值格式。此外,还证明了该方案同时保持了质量和能量守恒定律。其次,分析了数值格式的稳定性和收敛性。最后进行了数值实验,结果表明了理论结果的正确性和保守格式的有效性。
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引用次数: 0
Adaptive neural-domain refinement for solving time-dependent differential equations 求解时变微分方程的自适应神经域细化
Pub Date : 2023-10-25 DOI: 10.1186/s13662-023-03789-x
Toni Schneidereit, Michael Breuß
Abstract A classic approach for solving differential equations with neural networks builds upon neural forms, which employ the differential equation with a discretisation of the solution domain. Making use of neural forms for time-dependent differential equations, one can apply the recently developed method of domain segmentation. That is, the domain may be split into several subdomains, on which the optimisation problem is solved. In classic adaptive numerical methods, the mesh as well as the domain may be refined or decomposed, in order to improve the accuracy. Also, the degree of approximation accuracy may be adapted. Therefore, it is desirable to transfer such important and successful strategies to the field of neural-network-based solutions. In the presented work, we propose a novel adaptive neural approach to meet this aim for solving time-dependent problems. To this end, each subdomain is reduced in size until the optimisation is resolved up to a predefined training accuracy. In addition, while the neural networks employed are by default small, we propose a means to adjust also the number of neurons in an adaptive way. We introduce conditions to automatically confirm the solution reliability and optimise computational parameters whenever it is necessary. Results are provided for several initial-value problems that illustrate important computational properties of the method.
用神经网络求解微分方程的经典方法是建立在神经形式的基础上的,它采用微分方程的解域离散化。利用时变微分方程的神经形式,可以应用最近发展起来的区域分割方法。也就是说,可以将域划分为若干子域,在这些子域上解决优化问题。在经典的自适应数值方法中,为了提高精度,可以对网格和区域进行细化或分解。此外,可以调整近似精度的程度。因此,将这些重要而成功的策略转移到基于神经网络的解决方案领域是很有必要的。在本文中,我们提出了一种新的自适应神经方法来解决时间相关问题。为此,每个子域的大小被减小,直到优化被解决到预定义的训练精度。此外,虽然所使用的神经网络默认是小的,但我们提出了一种自适应方式调整神经元数量的方法。我们引入条件来自动确认解的可靠性,并在必要时优化计算参数。给出了几个初值问题的结果,说明了该方法的重要计算性质。
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引用次数: 0
Universal approximation property of a continuous neural network based on a nonlinear diffusion equation 基于非线性扩散方程的连续神经网络的普遍逼近性质
Pub Date : 2023-10-25 DOI: 10.1186/s13662-023-03787-z
Hirotada Honda
Abstract Recently, differential equation-based neural networks have been actively studied. This paper discusses the universal approximation property of a neural network that is based on a nonlinear partial differential equation (PDE) of the parabolic type. Based on the assumption that the activation function is non-polynomial and Lipschitz continuous, and applying the theory of the difference method, we show that an arbitrary continuous function on any compact set can be approximated using the output of the network with arbitrary precision. Additionally, we present an estimate of the order of accuracy with respect to △ t and △ x .
近年来,基于微分方程的神经网络得到了积极的研究。本文讨论了一类基于抛物型非线性偏微分方程的神经网络的普遍逼近性质。基于激活函数是非多项式和Lipschitz连续的假设,应用差分法理论,证明了任意紧集上的任意连续函数可以用网络的输出以任意精度逼近。此外,我们提出了关于△t和△x的精度阶数的估计。
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引用次数: 0
Bifurcation and chaos in a discrete Holling–Tanner model with Beddington–DeAngelis functional response 具有Beddington-DeAngelis函数响应的离散Holling-Tanner模型的分岔和混沌
Pub Date : 2023-10-23 DOI: 10.1186/s13662-023-03788-y
Run Yang, Jianglin Zhao
Abstract The dynamics of a discrete Holling–Tanner model with Beddington–DeAngelis functional response is studied. The permanence and local stability of fixed points for the model are derived. The center manifold theorem and bifurcation theory are used to show that the model can undergo flip and Hopf bifurcations. Codimension-two bifurcation associated with 1:2 resonance is analyzed by applying the bifurcation theory. Numerical simulations are performed not only to verify the correctness of theoretical analysis but to explore complex dynamical behaviors such as period-6, 7, 10, 12 orbits, a cascade of period-doubling, quasi-periodic orbits, and the chaotic sets. The maximum Lyapunov exponents validate the chaotic dynamical behaviors of the system. The feedback control method is considered to stabilize the chaotic orbits. These complex dynamical behaviors imply that the coexistence of predator and prey may produce very complex patterns.
研究了具有Beddington-DeAngelis泛函响应的离散Holling-Tanner模型的动力学问题。导出了模型的不动点的持久性和局部稳定性。利用中心流形定理和分岔理论证明了该模型可以发生翻转分岔和Hopf分岔。应用分岔理论分析了与1:2共振相关的共维二分岔。数值模拟不仅验证了理论分析的正确性,而且探索了复杂的动力学行为,如周期6,7,10,12轨道,周期倍级联,准周期轨道和混沌集。最大李雅普诺夫指数验证了系统的混沌动力学行为。采用反馈控制方法稳定混沌轨道。这些复杂的动态行为暗示着捕食者和猎物的共存可能会产生非常复杂的模式。
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引用次数: 0
Stability and dynamics of a stochastic discrete fractional-order chaotic system with short memory 具有短记忆的随机离散分数阶混沌系统的稳定性和动力学
Pub Date : 2023-10-10 DOI: 10.1186/s13662-023-03786-0
Jie Ran, Jixiu Qiu, Yonghui Zhou
Abstract In this paper, a stochastic discrete fractional-order chaotic system with short memory is proposed, which possesses two equilibrium points. With the help of the Lyapunov function theory, some sufficient conditions for the stability in probability of the two equilibrium points are given. Secondly, the effects of fractional order and memory steps on the stability of the system are discussed. Finally, the path dynamical behavior of the system is investigated using numerical methods such as Lyapunov exponents, bifurcation diagram, phase diagram, and 0–1 test. The numerical simulation results validate the findings.
摘要提出了一种具有两个平衡点的随机离散短记忆分数阶混沌系统。利用李雅普诺夫函数理论,给出了两个平衡点概率稳定的充分条件。其次,讨论了分数阶和记忆步长对系统稳定性的影响。最后,利用李雅普诺夫指数、分岔图、相图和0-1检验等数值方法研究了系统的路径动力学行为。数值模拟结果验证了上述结论。
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引用次数: 0
Algorithms for coupled Burgers’ equations by sharing characteristic curves within BSLM BSLM内共享特征曲线耦合Burgers方程的算法
Pub Date : 2023-10-09 DOI: 10.1186/s13662-023-03785-1
Soyoon Bak, Yonghyeon Jeon
Abstract This paper introduces a new perspective of the traditional view on the velocity of each physical particle in the coupled Burgers’ equation in the backward semi-Lagrangian method (BSLM). The proposed methods reduce the number of Cauchy problems to be solved by observing a single virtual characteristic curve with a velocity. This can drastically reduce the computational cost of determining the departure point. Then, we solve the derived system reflected by the single virtual characteristic curve. Moreover, an efficient strategy for the derived linear system of equations is provided. Four examples are tested to demonstrate the adaptability and efficiency of the proposed method. The test results show that the proposed method has third- and fourth-order accuracy in time and space, respectively. In addition, compared with the existing method of solving the problem along two particles with different velocities, we confirm that the proposed method significantly reduces computational cost while maintaining accuracy well.
摘要本文介绍了后向半拉格朗日方法(BSLM)中耦合Burgers方程中各物理粒子速度的传统观点的新视角。所提出的方法减少了通过观察单个具有速度的虚拟特征曲线来求解柯西问题的数量。这可以大大减少确定出发点的计算成本。然后,求解由单个虚特性曲线反映的导出系统。此外,还给出了一种有效的求解线性方程组的策略。通过四个算例验证了该方法的适应性和有效性。实验结果表明,该方法在时间和空间上分别具有三阶和四阶精度。此外,与现有沿两个不同速度粒子求解问题的方法相比,我们证实了该方法在保持精度的同时显著降低了计算成本。
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引用次数: 0
Forward invariant set preservation in discrete dynamical systems and numerical schemes for ODEs: application in biosciences 离散动力系统的前向不变量集保持和ode的数值格式:在生物科学中的应用
Pub Date : 2023-09-22 DOI: 10.1186/s13662-023-03784-2
Roumen Anguelov, Jean M.-S. Lubuma
Abstract We present two results on the analysis of discrete dynamical systems and finite difference discretizations of continuous dynamical systems, which preserve their dynamics and essential properties. The first result provides a sufficient condition for forward invariance of a set under discrete dynamical systems of specific type, namely time-reversible ones. The condition involves only the boundary of the set. It is a discrete analog of the widely used tangent condition for continuous systems ( viz. the vector field points either inwards or is tangent to the boundary of the set). The second result is nonstandard finite difference (NSFD) scheme for dynamical systems defined by systems of ordinary differential equations. The NSFD scheme preserves the hyperbolic equilibria of the continuous system as well as their stability. Further, the scheme is time reversible and, through the first result, inherits from the continuous model the forward invariance of the domain. We show that the scheme is of second order, thereby solving a pending problem on the construction of higher-order nonstandard schemes without spurious solutions. It is shown that the new scheme applies directly for mass action-based models of biological and chemical processes. The application of these results, including some numerical simulations for invariant sets, is exemplified on a general Susceptible-Infective-Recovered/Removed (SIR)-type epidemiological model, which may have arbitrary large number of infective or recovered/removed compartments.
摘要给出了离散动力系统的分析结果和连续动力系统的有限差分离散化结果,它们保持了系统的动力学性质和基本性质。第一个结果为特定类型的离散动力系统(即时间可逆系统)下集合的前向不变性提供了充分条件。这个条件只涉及集合的边界。它是连续系统中广泛使用的切线条件的离散模拟(即向量场指向集合的边界或与集合的边界相切)。第二个结果是由常微分方程系统定义的动力系统的非标准有限差分格式。NSFD格式既保持了连续系统的双曲平衡,又保持了系统的稳定性。此外,该方案是时间可逆的,并且通过第一个结果继承了连续模型的域的前向不变性。我们证明了该格式是二阶的,从而解决了一个悬而未决的无假解的高阶非标准格式的构造问题。结果表明,新方案直接适用于基于质量作用的生物和化学过程模型。这些结果的应用,包括对不变集的一些数值模拟,在一般的易感感染/恢复/去除(SIR)型流行病学模型上举例说明,该模型可能具有任意数量的感染或恢复/去除区室。
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Advances in continuous and discrete models
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