The Fear Effect on a Food Chain Prey-Predator Model Incorporating a Prey Refuge and Harvesting

Alabacy, Zina; Majeed, Azhar Abbas

doi:10.1088/1742-6596/1804/1/012077

Cited by 8 publications

(5 citation statements)

References 11 publications

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“…Considering that the evolution of prey-predators system related to both the current moment and some past state of the species, and each species has different degree of dependence on the past, incommensurate fractional-orders are added to the system (8). Otherwise, inspired by the reference [16], the prey's fear effect is thought about not only mature predator but also immature predator.…”

Section: Model Descriptionmentioning

confidence: 99%

“…Let q 1 = 1, q 2 = 1, q 3 = 1 and k 1 = 0, the system (38) becomes an integer-order system corresponding to system (8). The coexistence equilibrium point is (0.2131, 0.0247, 0.1974), and the bifurcation critical point is (τ 0 = 22.77, ω 0 = 0.0501), which is consistent with the results in Wang [35].…”

Section: Case 3 the Influence Of Fractional-orders On The Stability R...mentioning

confidence: 99%

“…The prey refuge is a suitable method to protect the prey population [5]. Prey-predator models with prey refuge are brought into focus and many worthy results are obtained [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

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Hopf Bifurcation and Control of a Fractional-Order Delay Stage Structure Prey-Predator Model with Two Fear Effects and Prey Refuge

2022

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A generalized delay stage structure prey-predator model with fear effect and prey refuge is considered in this paper via introducing fractional-order and fear effect induced by immature predators. Hopf bifurcation and control of this system are investigated though regarding the delay as the parameter. Firstly, by using the method of linearization and Laplace transform, the roots of the characteristic equation of the linearized system of the original system are discussed, and the sufficient conditions for the system exhibits an unstable state of symmetrical periodic oscillation (Hopf bifurcation) are explored. Secondly, a linear delay feedback controller is added to the system to increase the stability domain successfully. Thirdly, numerical simulations are performed to validate the theoretical analysis, and the various impacts on the dynamical behavior of the system occurring by fear effects, prey refuge, and each fractional-order are illustrated, respectively. Furthermore, the influence of feedback gain on the bifurcation critical point is analyzed. Finally, an analysis based on the results and in-depth research about this system under the biological background is stated in the conclusion.

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Section: Model Descriptionmentioning

confidence: 99%

Section: Case 3 the Influence Of Fractional-orders On The Stability R...mentioning

confidence: 99%

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Hopf Bifurcation and Control of a Fractional-Order Delay Stage Structure Prey-Predator Model with Two Fear Effects and Prey Refuge

2022

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“…Wavelets have a great role in image processing through computer vision [1]- [4], such as compression [5]- [8], noise reduction, and image retrieval without losing the original image qualities [9]- [12]. This helped to identify faces and engineering and scientific applications because they are characterized by very important features which are the frequencies and time-dependent [13]- [15].…”

Section: Introductionmentioning

confidence: 99%

The effectiveness of the Hermite wavelet discrete filter technique in modify a convolutional neural network for person identification

Tahir

Abdulrahman²

2023

IJEECS

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Classification is of great importance in the field of image processing, and convolutional neural networks (CNNs) have achieved great success in this field. Although CNN has proven to be a powerful technology for image recognition problems, it has failed in complex situations involving many realworld applications (for example, visual monitoring and automated driver assistance). Where it is difficult to detect a human in a series of images for various reasons. One of these reasons is the difference in the size of the human body, the height of the platform to which the camera is attached during the task of capturing accurate images, and the short training time in using the cameras, all of which are important factors to consider for the robustness and effectiveness of the human classification system. In this paper, a new deep CNN-based learning model is designed based on a new discrete waveform transformation (DWT) derived from discrete Hermit wavelet transform (DHWT) instead of modular wavelet, and the second stage is to train the convolutional neural network Hermit wavelets (HWCNN) is the most accurate and efficient deep learning.

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“…Based on a review of the existing literature, it appears that most of the authors comprise their models with the combined effects of fear-harvesting [10,32], fear-refuge [8,9], harvesting-refuge [33,34], and studied their models. In a recent study, Alabacy [35] developed a three-species model with the combined effects of fear-refuge-harvesting. Based upon the above literatures, we develop a prey-predator model incorporating fear, refuge and harvesting, and study the model with and without seasonality.…”

Section: Introductionmentioning

confidence: 99%

An autonomous and nonautonomous predator–prey model with fear, refuge, and nonlinear harvesting: Backward, Bogdanov–Takens, transcritical bifurcations, and optimal control

Mondal

Sarkar

Ghosh

2023

Math Methods in App Sciences

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In recent research, fear, refuge, and harvesting have been highlighted, but their combined impact must also be explored. We investigate the combined effects of these three ecologically important factors in the context of a prey–predator system using Holling type II as an interaction term. By using the parametric conditions, we can determine the existence of biologically feasible equilibria with their local and global stability. We investigate transcritical, Saddle‐node, Hopf, backward, Bogdanov–Takens bifurcations about different equilibria theoretically and numerically. We observe that the system is stable for lower and higher values of catchability effect and harvesting parameters. And the system shows stable behavior for a high value of fear and refuge parameters. Our model is extended by considering fear, refuge, and harvesting as time‐dependent parameters. Nonautonomous systems exhibit periodic solutions when the corresponding autonomous system is stable. Further, the nonautonomous system shows complex dynamics such as higher periods, chaos and bursting patterns whenever the associated autonomous system goes through limit cycle oscillations.

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The Fear Effect on a Food Chain Prey-Predator Model Incorporating a Prey Refuge and Harvesting

Cited by 8 publications

References 11 publications

Hopf Bifurcation and Control of a Fractional-Order Delay Stage Structure Prey-Predator Model with Two Fear Effects and Prey Refuge

Hopf Bifurcation and Control of a Fractional-Order Delay Stage Structure Prey-Predator Model with Two Fear Effects and Prey Refuge

The effectiveness of the Hermite wavelet discrete filter technique in modify a convolutional neural network for person identification

An autonomous and nonautonomous predator–prey model with fear, refuge, and nonlinear harvesting: Backward, Bogdanov–Takens, transcritical bifurcations, and optimal control

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