Computational modelling
Seyed Hamid Emadi; Abolfazl Sadeghian; Mozhde Rabbani; hassan dehghan dehnavi
Abstract
We consider a continuous model of the optimal control of the customer dynamics based on marketing policies as a non-autonomous system of ODEs. The model tracks the history of the simultaneous changes from the beginning to the current time for the evolution of the company’s regular, referral, and ...
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We consider a continuous model of the optimal control of the customer dynamics based on marketing policies as a non-autonomous system of ODEs. The model tracks the history of the simultaneous changes from the beginning to the current time for the evolution of the company’s regular, referral, and potential customers. We then present a new supervised machine learning algorithm for the numerical simulation of the problem. The proposed learning algorithm implements a polynomial kernel to simplify the formulation of the method. To avoid computational complexity, the Bernstein kernels are used to get a simple optimization marketing strategy by using the support vector regression in least-squares framework. Some numerical experiments are carried out to support the proposed model and the method. The method provides approximate numerical results with high accuracy by kernels of polynomials of low degree. The running time of the method is also illustrated versus the increasing number of training points to see the polynomial behavior of the running time.
Computational modelling
Eshetu Dadi Gurmu; Boka Kumsa Bole; Purnachandra Rao Koya
Abstract
In this paper, optimal control problem is applied to Human Papillomavirus (HPV) and Herpes Simplex Virus type 2 (HSV-2) coinfection model formulated by a system of ordinary differential equations. Optimal control strategy is employed to study the effect of combining different intervention strategy on ...
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In this paper, optimal control problem is applied to Human Papillomavirus (HPV) and Herpes Simplex Virus type 2 (HSV-2) coinfection model formulated by a system of ordinary differential equations. Optimal control strategy is employed to study the effect of combining different intervention strategy on the transmission dynamics of HPV-HSV-II coinfection diseases. The necessary conditions for the existence of the optimal controls are established using Pontryagin’s Maximum Principle. Optimal control systems were performed with help of Runge-Kutta forward-backward sweep numerical approximation method. Finally, numerical simulation illustrated that a combination of all controls is the most effective strategy to minimize the disease from the community. The results shows that the size of infectious population are minimized by using different control strategies.
