In this paper, a discretization of a three-dimensional fractional-order prey-predator model has been investigated with Holling type III functional response. All its fixed points are determined; also, their local stability is investigated. We extend the discretized system to an optimal control problem to get the optimal harvesting amount. For this, the discrete-time Pontryagin’s maximum principle is used. Finally, numerical simulation results are given to confirm the theoretical outputs as well as to solve the optimality problem.

This work aims to analyze a three-dimensional discrete-time biological system, a prey-predator model with a constant harvesting amount. The stage structure lies in the predator species. This analysis is done by finding all possible equilibria and investigating their stability. In order to get an optimal harvesting strategy, we suppose that harvesting is to be a non-constant rate. Finally, numerical simulations are given to confirm the outcome of mathematical analysis.

لا يستطيع كل كائن حي أو كيان اجتماعي أداء دوره الذي يفترض أن يقوم به ما لم يمتلك الوسائل الكافية والضرورية لأداء ذلك الدور قال سبحانه وتعالى ((قال ربنا الذي أعطى كل شيء خلقه ثم هدى – طه 50)).

والنشاط الاقتصادي كجزء من الكيان الكلي للمجتمع لا يختلف عن هذه القاعدة، إذ عندما يراد من النظام الاقتصادي أداء دور فاعل فلا غنى له عن الوسائل التي تمكنه من أداء دوره المنشود. للنظام الاقتصادي مجمو

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

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