Results in Control and Optimization最新文献

Extremists are increasingly using social media to recruit and radicalize other users and increase their money. Terrorists can use popular social networks accounts and perform their activities in a hidden way. So, it is crucial to create a fruitful mechanism for controlling the spread of misinformation. Otherwise, a large number of people can mislead by this terrorist activity by joining them. Here, we propose malicious news spreading model incorporating hidden attackers of a social network. A threshold is defined for deciding the extinction of malicious news from a social network. Here, we show the importance of network alertness and activity of cybersecurity agencies in the modified model. Moreover, we obtained the optimal values of the control parameters for emergencies.

In this paper, we explore the property of being a cordial graphic and establish that it corresponds to an Alexandroff topological space. We analyze how the characteristics of cordial graphs align with the principles of Alexandroff topology and provide insights into their topological structure.

In order to effectively manage their customers, businesses need to thoroughly analyze the costs and advantages associated with various alternative expenditures and investments and determine the most effective way to allocate resources to marketing and sales activities over time. Those in charge of making decisions will reap the benefits of decision support models that estimate the value of the customer portfolio and tie expenses to customers' purchasing behavior. In the current work, various machine learning algorithms such as Decision Tree (DT), Random Forest (RT), Logistic Regression (LR), Support Vector Machines (SVM), and gradient boosting are used to predict customer behavior. The evaluation criteria considered in the work include precision, recall, F1-Score, and ROC-AUC. The accuracy values obtained for DT, RT, LR, SVM, and gradient boosting are 0.787, 0.806, 0.826, 0.826, and 0.823, respectively. The results emphasize RT and LR's good performance, while the values of 0.620, 1, 0.766, and 0.878 for the precision, recall, F1-score, and ROC-AUC score outperform the rest. The novelty of this work lies in employing a comprehensive set of machine learning algorithms to predict customer behavior, with a particular emphasis on the superior performance of RF and LR models, as demonstrated by their high precision, recall, F1-score, and ROC-AUC values.

A novel method has been introduced to dissolve optimal control problems in systems governed by third-kind Volterra integral equations. This method utilizes Krall–Laguerre Polynomials as a basis function for expanding functions. By transforming the optimal control problem governed by third-kind Volterra integral equations (OCVIE3k) into a nonlinear programming problem (NLP), the solution process is significantly simplified. This approach involves converting the original problem into a more manageable form, which can be solved using established optimization techniques. The effectiveness and reliability of this proposed method are evaluated by comparing its outcomes to exact solutions when available.

This article studies the action of predators and the predator-dependent functional response in the fishery resource model. We employ the Atangana–Baleanu–Caputo fractional derivative to study the proposed fractional fishery resource model in the presence of predators with Crowley–Martin functional response. We present a theoretical and numerical analysis of the governing nonlinear differential equations of the model consisting of the biomass density of the fish population inside the unrestricted fishing zone, the biomass density of the fish population inside the reserve or restricted fishing zone, and the predator population. Using the fixed point theory and nonlinear analysis, we establish the existence and uniqueness results of the proposed $\mathrm{ABC}$ fractional fishery resource model. We establish stability analysis of the fishery model using the Ulam–Hyers stability approach. The numerical scheme of the fractional Adams–Bashforth method is provided and the approximate solutions for the model under consideration are given and discussed. We observe that an increase in the fish capturing rates increases the size of the predator population and reduces the fish subpopulations. To maintain a high number of fish species, we recommend a control measure to reduce the fish capturing rate by the predators.

This study develops and analyzes the within-host dynamics of malaria parasite infection with optimal control strategies. We considered both the blood and liver stages of the malaria infection, taking into account the immunological response against the infection. The basic reproduction number, which indicates the potential spread of the parasite is evaluated. The parasite-free equilibrium point is locally and globally asymptotically stable when the basic reproduction is less than a unit. Sensitivity analysis reveals that the invention rate of red blood cells and the average number of merozoites per rupture infected red blood cell are the most influential parameters of the model. Furthermore, to investigate the most effective measurement of malaria parasite infection, we performed the optimal control strategies. The pre-erythrocytic vaccine, blood-stage vaccine, primary tissue schizontocides, blood schizontocides, and gametocytocidal drugs are incorporated as control measures. The controls are implemented to minimize the infected hepatocytes, infected red blood cells, gametocytes, and merozoites in the human host, as well as the associated costs. Pontryagin’s Minimum Principle is applied to establish optimal control strategies against infected red blood cells, infected hepatocytes, and malaria parasites. Several simulation situations are conducted to assess the analytical results and determine the effective control intervention measures. The results indicate that administering all four controls simultaneously would eradicate the prevalence of malaria infection in the human host.