Discrete Dynamics in Nature and Society

Journal Information
ISSN / EISSN: 10260226 / 1607887X
Published by: Hindawi Limited
Total articles ≅ 4,440

Latest articles in this journal

Aeshah A. Raezah
Published: 21 November 2022
Discrete Dynamics in Nature and Society, Volume 2022, pp 1-24; https://doi.org/10.1155/2022/2106910

Dengue is an epidemic disease rapidly spreading throughout many parts of the world, which is a serious public health concern. Understanding disease mechanisms through mathematical modeling is one of the most effective tools for this purpose. The aim of this manuscript is to develop and analyze a dynamical system of PDEs that describes the secondary infection caused by DENV, considering (i) the diffusion due to spatial mobility of cells and DENV particles, (ii) the interactions between multiple target cells, DENV, and antibodies of two types (heterologous and homologous). Global existence, positivity, and boundedness are proved for the system with homogeneous Neumann boundary conditions. Three threshold parameters are computed to characterize the existence and stability conditions of the model’s four steady states. Via means of Lyapunov functional, the global stability of all steady states is carried out. Our results show that the uninfected steady state is globally asymptotically stable if the basic reproduction number is less than or equal to unity, which leads to the disappearance of the disease from the body. When the basic reproduction number is greater than unity, the disease persists in the body with an active or inactive immune antibody response. To demonstrate such theoretical results, numerical simulations are presented.
Yan Hou, Haisheng Yu
Published: 18 November 2022
Discrete Dynamics in Nature and Society, Volume 2022, pp 1-16; https://doi.org/10.1155/2022/5622961

The uncertainty of emergencies makes the emergency procurement face many risks, so the risk management is particularly important of the emergency procurement. The risk attitude of decision makers will significantly affect the decision-making of risk management. In this paper, the risk management problem with different risk attitudes of emergency procurement consisting of dual-source suppliers and the single government is studied, and a government-led Stackelberg game is used to analyze the risks of each link to establish an emergency procurement model under the option contract, and the optimal decision-making is obtained. The effects of reserve period, risk avoidance coefficient, and probability of emergency on optimal decision-making are analyzed with different risk attitude. Moreover, we investigate the coordination of the government-led supply chain coordination under the risk aversion and risk-neutral conditions of emergency supply chain participants. The results show that the model can control the risk while reducing the cost of government procurement and ensuring the revenue of suppliers. Finally, the influence of each parameter on the optimization decision is verified by a numerical example.
, Xiuhua Fu,
Published: 17 November 2022
Discrete Dynamics in Nature and Society, Volume 2022, pp 1-11; https://doi.org/10.1155/2022/8190688

The high-speed development of mobile broadband networks and IoT applications has brought about massive data transmission and data processing, and severe traffic congestion has adversely affected the fast-growing networks and industries. To better allocate network resources and ensure the smooth operation of communications, predicting network traffic becomes an important tool. We investigate in detail the impact of variable sampling rate on traffic prediction and propose a high-speed traffic prediction method using machine learning and recurrent neural networks. We first investigate a VSR-NLMS adaptive prediction method to perform time series prediction dataset transformation. Then, we propose a VSR-LSTM algorithm for real-time prediction of network traffic. Finally, compared with the traditional traffic prediction algorithm based on fixed sampling rate (FSR-LSTM), we simulate the prediction accuracy of the VSR-LSTM algorithm based on the variable sampling rate proposed. The experiment shows that VSR-LSTM has higher traffic prediction accuracy because its sampling rate varies with the traffic.
Qun Zhang, Junjie Lin, Wenyue Wei, Yuanzhu Wei
Published: 16 November 2022
Discrete Dynamics in Nature and Society, Volume 2022, pp 1-12; https://doi.org/10.1155/2022/3250863

Marine ecological aquaculture is considered a robust scientific farming model, but it has not been widely promoted in China. Although some studies have examined stakeholders’ interests in ecological transformation, few studies to date have analyzed the interaction mechanism of the stakeholders in ecological transformation. Therefore, drawing on evolutionary game theory, this study analyzed the different behavioral strategies and evolutionary mechanisms of the government, marine aquaculture farmers, and aquatic enterprises engaged in marine farming processes. Furthermore, a numerical simulation was conducted to evaluate the rationality of the theoretical model. The results show that several factors affected the ecological transformation of mariculture. Government subsidies reduced farmers’ and aquatic enterprises’ costs of adopting ecological farming. The government’s increasing fines for aquaculture pollution slowed down the speed of the system to a stable point. The cost of adopting ecological farming by farmers and aquatic enterprises will affect their decision to adopt or invest in it. The increase in the market price of eco-aquatic products helped accelerate the ecological transformation of mariculture. The brand effect obtained by aquatic enterprises by investing in ecological farming helped increase participation to further improve this practice. In terms of policy implications, we recommend the promotion and guidance of marine aquaculture technology, government support and investment, environmental control of the aquaculture industry, and brand building of eco-aquatic products to transform and upgrade marine aquaculture farming.
Yang Liu, Qingtian Wang, Haitao Liu, Jiaying Zong, Fengyi Yang
Published: 15 November 2022
Discrete Dynamics in Nature and Society, Volume 2022, pp 1-11; https://doi.org/10.1155/2022/4955498

Edge Intelligence, which blends Artificial Intelligence (AI) with Radio Access Network (RAN) and edge computing, is recommended as a crucial enabling technology for 6G to accommodate intelligent and efficient applications. In this study, we proposed Edge Intelligent Radio Access Network Architecture (EIRA) by introducing new intelligence modules, which include broadband edge platforms that allow policies to interact with virtualized RAN for various applications. We also developed a Markov chain-based RAN Intelligence Control (RIC) scheduling policy for allocating intelligence elements. Experimental results justified that the virtualized RAN delivers on its performance promises in terms of throughput, latency, and resource utilization.
Ruijing Wang,
Published: 10 November 2022
Discrete Dynamics in Nature and Society, Volume 2022, pp 1-7; https://doi.org/10.1155/2022/8758294

In this article, we use a finite difference scheme to discretize the Cahn-Hilliard equation with the space step size h . We first prove that this semidiscrete system inherits two important properties, called the conservation of mass and the decrease of the total energy, from the original equation. Then, we show that the semidiscrete system has an attractor on a subspace of N+1 . Finally, the convergence of attractors is established as the space step size h of the semidiscrete Cahn-Hilliard equation tends to 0.
Published: 8 November 2022
Discrete Dynamics in Nature and Society, Volume 2022, pp 1-13; https://doi.org/10.1155/2022/1906435

This paper designs and implements a methodology to model the evolution of the COVID-19 pandemic, produced by the SARS-CoV-2 virus, in what was called the first wave in Chile, which lasted from March 2 to 31 October 2020. The models are based on sigmoidal growth curves and can be used to predict the number of daily infections and deaths in future days, making them a useful tool for sanitary authorities to manage an epidemic. The methodology is applied to the entire country and to each of its most affected regions. In addition, the dynamics of these models allow it to be nurtured with the new information that is being produced and forecast a tentative date on which there would be some control over the pandemic. Moreover, these models allow for predicting the total number of infected and deceased people at the time the pandemic is under control. However, the simplicity of these models, which consider only the accumulated data of those infected and deceased, does not contemplate an intervention analysis such as vaccinations, which, as is known, are being effective in controlling the pandemic.
, Zhaoyang Tian, Guilin Chang
Published: 3 November 2022
Discrete Dynamics in Nature and Society, Volume 2022, pp 1-16; https://doi.org/10.1155/2022/7561841

With the gradual retirement of the first batch of new energy vehicles in recent years, determining the optimal recycling mode has become an urgent concern. Considering the closed-loop supply chain, the government subsidy system, and different market power structures, this paper studies new energy vehicle recycling decisions and supply chain contract coordination. The results show that given an increase in government subsidies, the profit of the dominant agent in the closed-loop supply chain will be higher than that of the follower, and an increase in wholesale and recovery prices may lead to an increase in sales prices. In addition, the effect of government subsidies on battery recovery is better in cases of vehicle manufacturer dominance than in those of battery manufacturer dominance. Finally, when a battery manufacturer is in the dominant position, a revenue sharing contract can incentivize supply chain coordination; when a vehicle manufacturer is in the dominant position, a two-part tariff contract can realize coordination in the supply chain.
Published: 3 November 2022
Discrete Dynamics in Nature and Society, Volume 2022, pp 1-16; https://doi.org/10.1155/2022/9169185

Fractional Langevin system has great advantages in describing the random motion of Brownian particles in complex viscous fluid. This manuscript deals with a delayed nonlinear fractional Langevin system with nonsingular exponential kernel. Based on the fixed point theory, some sufficient criteria for the existence and uniqueness of solution are established. We also prove that this system is UH- and UHR-stable attributed to the nonlinear analysis and inequality techniques. As applications, we provide some examples and simulations to illustrate the availability of main findings.
Riquan Yao, Shaojun Jin, Cong Wei,
Published: 2 November 2022
Discrete Dynamics in Nature and Society, Volume 2022, pp 1-12; https://doi.org/10.1155/2022/2182748

The grey model, which is abbreviated as GM (1, 1), has been widely applied in the fields of decision and prediction, particularly in the prediction of time series with few observations, referred to as the poor information and small sample in the literature related to grey model. Previous studies focus on improving the accuracy of prediction but pay less attention to the robustness of the grey model to outliers, which often occur in practice due to an incorrect record by chance or an accidental failure in equipment. To fill that void, we develop a robust grey model, whose structural parameters are obtained from the least trim squares, to forecast Chinese electricity demand. Also, we use the last value in the first-order accumulative generating time series as the initial value, according to the new information priority criterion. We name the novel grey model, proposed in this paper, the novel robust grey model integrating the new information priority criterion, which could be abbreviated as NIPC-GM (1, 1). In addition, we introduce a novel approach, that is, the bootstrapping test, to investigate the robustness against outliers for the novel robust grey model and the classical grey model, respectively. Using the data on Chinese electricity demand from 2011 to 2021, we find that not only does the novel robust grey model integrating the new information priority criterion have a better robustness to outliers than the classical grey model, but it also has a higher accuracy of prediction than the classical grey model. Finally, we apply the novel robust grey model integrating the new information priority criterion to forecasting the future values in Chinese electricity demand during the period 2022 to 2025. We see that Chinese electricity demand would continue to rise in the next four years.
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