Results in Control and Optimization最新文献

While Unmanned Aerial Vehicles (UAVs) have found applications across numerous industries, they still remain vulnerable to various cybersecurity challenges. Different types of cyberattacks target UAVs. Early detection of these cyberattacks is considered the most important step in ensuring the cybersecurity of UAVs. In this article, an artificial intelligence method based on machine learning was developed for detecting different types of Denial of Service (DoS) attacks targeting the UAV network. Initially in this work, feature selection methods are implemented to select the most important features. Then, machine learning methods are used to classify attacks. According to the conducted experiments, the proposed method outperformed others with an accuracy of 99.51 % and a prediction time of 0.1 s. Additionally, a novel dataset is used in this work, which offers several advantages. The dataset was created within a real-world environment rather than a simulated one. Furthermore, the data were collected within a 5G network.

In this study, we developed and analyzed a compartmental epidemic model and a system model that incorporate vaccination, elimination, and quarantine techniques, with a saturated incidence rate, by theoretical and numerical means. The model is described by a system of four nonlinear differential equations. Our analysis included determining the reproduction number $R_q$ and examining equilibrium solutions. The outcomes of the disease are identified through the threshold $R_q$. When $R_q<1$, the disease-free equilibrium is globally asymptotically stable, as proved by the LaSalle invariance principle and disease extinction analysis. However, using the Routh–Hurwitz criterion, we have proved that the disease-free equilibrium is not stable, and when $R_q>1$, the unique endemic equilibrium is asymptotically stable locally. The stability of the endemic and disease-free equilibria globally has been examined using the Routh–Hurwitz and Dulac criteria. Subsequently, numerical simulations were utilized to illustrate the theoretical findings effectively.

This paper examines the analysis of some rational-type contractions within the context of extended b-metric spaces, establishes a theoretical foundation for rational-type contractions and demonstrates their application in Volterra integral inclusions and Urysohn integral equations. Some examples are provided for the authenticity of the findings.

Sufficient conditions for controllability of impulsive nonlinear integro-differential equations with $\psi$-Hilfer fractional derivative are established. The result are obtained by using fractional calculus and Schaefer’s fixed point theorem. Finally, a numerical examples are then provided to demonstrate the outcomes.

Diabetes Mellitus (DM) is emerging as a global concern, affecting people from early ages to adulthood and positioning itself as one of the leading causes of mortality worldwide. The post-COVID-19 era has been characterized by notable progress in the domains of medicine, science, and engineering, creating a favorable atmosphere for the investigation of innovative solutions. The present manuscript aims to investigate the problem of glucose regulation in adults diagnosed with Type 1 Diabetes mellitus (T1D) using a two-degree-of-freedom robust controller technique. A physiological mathematical model involving individuals with T1D serves as the foundation for the proposed closed-loop technique. The control algorithm approach successfully maintains safe glycemic levels in a virtual population of 10 adults using a sophisticated, well-known physiological T1D simulator. We evaluated this with continuous 24-hour simulations. Simulation results support the practicality of the presented approach, and we further validate it using a statistical analysis that incorporates a probability density function and control variability grid analysis (CVGA). Despite being a theoretical and simulation-based methodology, the results of this study demonstrate promise, offering promising opportunities for developments in the field of artificial pancreas technology using Mexican technology.

According to the World Health Organization’s guidelines, a two-year mandatory breastfeeding period is strongly recommended, supported by research demonstrating its significant benefits in reducing childhood illnesses and mortality rates. The present study is designed to address this recommendation by focusing on a specific infection, namely rotavirus. Acknowledging this evidence, researchers recognize the need for a deeper understanding of the dynamics of rotavirus disease. In response, our study focuses on constructing and analyzing an SIR epidemic model uniquely designed for transmitting rotavirus in children. The model partitions the children population into three compartments: susceptible, infected, and recovered. To enhance precision, we further categorize susceptible children based on breastfeeding status and infected individuals based on infectious or non-infectious nature. This detailed categorization enables a thorough examination of rotavirus transmission dynamics. The proposed model analyzes two equilibria, disease-free and endemic, revealing local and global stability conditions determined by the basic reproduction number ($R_0$). Our exploration extends to local stability analysis for the endemic equilibrium when $R_0>1$ and global stability assessment using the Lyapunov theory under specific conditions. Subsequently, we employ optimal control theory through Pontryagin’s maximum principle to minimize the cost burden associated with disease control in children. Then, our work provides a sensitivity analysis of different parameters for the basic reproduction number to enhance our understanding of model dynamics. Finally, numerical simulations conducted with MATLAB and Python software validate our analytical findings, offering a comprehensive and practical assessment of the proposed model’s implications for controlling rotavirus transmission in children.

The optimization of the active control system is pivotal in achieving an acceptable performance level while minimizing control costs. The optimal location of actuators, efficient control force, and adequate vibration reduction are critical objectives in control system optimization. This study introduces a novel optimization algorithm, the Population-Guided and Modified Reference-Point Based Non-Dominated Sorting Genetic Algorithm-II (PMR-NSGA-II), tailored for actuator placement and tuning that incorporates input and output user preference. The analysis focuses on optimizing the vibration control of a 20-story steel frame building. The PMR-NSGA-II could reduce the computational expenses of three objectives optimization by guiding the initial population using prospective population prediction and orienting the search towards a reference point. The pre-calculated input energy distribution guides the determination of the prospective initial population. The reference point, along with the allowable drift and actuator capacity constraints, focuses the search process to efficiently obtain the Pareto fronts with less effort wasted to explore the less preferred areas in the search space. The non-dominated sorting and elitist operators are also employed to fasten the convergence. The structural analysis is conducted via non-linear time history analysis with seven ground motions considered. The PMR-NSGA-II exhibits significant computational efficiency in the active control system optimization. Results demonstrate that PMR-NSGA-II could provide the near-optimal solution closest to the reference point with a smaller population size and a faster convergence rate than the NSGA-II. The computational time per generation of the proposed PMR-NSGA-II is 1.36 to 2.43 times faster than NSGA-II for the seven ground motions analyzed. By applying PMR-NSGA-II, the number of individuals that need to be assessed to reach convergence is reduced by 50 % to 88 % compared to NSGA-II. Ultimately, the near-optimal configurations could significantly reduce the building responses and increase the performance level of the building based on FEMA 356 and ASCE 41 acceptance criteria.

The impulsive fractional differential equation of the Sobolev type, including deviating arguments, is the subject of the study. The analytic semigroup and fixed point approaches serve the purpose of determining the existence of the approximations. The fractional power of a closed linear operator concept is used to show how the approximation converges. To arrive at a unique approach, an approximation strategy is used. Our main conclusions are defined using an example.

The aim of this work is to provide a comprehensive analysis of the dynamics within an ecosystem characterized by interactions between prey and predators, through a combination of theoretical analysis and numerical simulation. The study investigates the impact of two pivotal effects: the “Hide-and-Escape” behavior exhibited by prey and the “Predation Skill Augmentation” strategy adopted by predators. Theoretical analysis identifies three equilibrium points, all of which show positive characteristics. Furthermore, local stability conditions are determined for each of these equilibrium points. The derivation of global stability conditions is also presented, and their validity and importance as local stability conditions for the coexistence point are demonstrated. In addition, Kolmogorov conditions for coexistence and extinction are verified, as well as local bifurcation analysis. For the validity of the results, a numerical simulation of the system using MATLAB is conducted.

In this article, we report a set of unique dynamic inequalities for different time scales that are based on delta-derivatives. These proposed inequalities prove to be useful tools for investigating both qualitative and quantitative facets of a class of time-scale dynamic equations, in addition to enhancing and extending several inequalities found in the literature. The introduced inequalities aid in a more thorough comprehension of the features of these equations, which involve an unknown function and its associated delta derivatives. The endpoint of this article includes numerical illustrations to emphasize the practical significance of the developed results.