Study of two species prey-predator model in imprecise environment with MSY policy under different harvesting scenario

Mahata, Animesh; Mondal, Sankar Prasad; Roy, Banamali; Alam, Shariful

doi:10.1007/s10668-021-01279-2

Cited by 16 publications

(4 citation statements)

References 49 publications

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“…Smithson and Verkuilen [5] discussed the applications of FS in social sciences. Mahata et al [6] investigated two species prey-predator models and Mahata et al [7] devised complex food chain modeling in an interval environment. Rosenfeld [8] invented the theory of fuzzy group which is a mathematical notion that extends the idea of a traditional subgroup to deal with ambiguity or uncertainty in the membership of components.…”

Section: Introductionmentioning

confidence: 99%

Bipolar complex fuzzy submodules

Alsuraiheed,

ur Rehman,

Khan

et al. 2024

Phys. Scr.

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In this manuscript, we interpret the theory of bipolar complex fuzzy submodule (BCFSM) of a provided classical module over a ring by utilizing the well-known notion of bipolar complex fuzzy set (BCFS). We also devise the sum of two BCFS and investigate its related proposition for studying a few fundamental properties of the initiated BCFSM. Moreover, we investigate the cartesian product of two BCFS for developing properties of BCFSM. We also investigate that if a BCFS Ӈ_1 is a BCFSM of Ӎ_1, then image Ӻ(Ӈ) is a BCFSM of Ӎ_2 and the preimage Ӻ^(-1) (Ӈ) is a BCFSM of Ӎ_1, where, Ӎ_1 and Ӎ_2 are two modules and Ӻ:Ӎ_1→Ӎ_2 is a module homomorphism.

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Section: Introductionmentioning

confidence: 99%

Bipolar complex fuzzy submodules

Alsuraiheed,

ur Rehman,

Khan

et al. 2024

Phys. Scr.

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“…In this paper, we focus on studying the advantages of using interval number biological parameters for prey-predator systems and the effect of certain model parameters on the system. Although some studies have explored the use of interval parameters in prey-predator models [16][17][18][19][20][21][22], our research offers new insights into the potential benefits of this approach. Ultimately, our findings can contribute to a better understanding and management of these vital ecosystems.…”

Section: Introductionmentioning

confidence: 99%

A three-component prey-predator system with interval number

Ghosh¹,

Santra²,

Mahapatra³

2023

Mathematical Modelling and Numerical Simulation With Applications

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This paper presents a three-component model consisting of one prey and two predator species using imprecise biological parameters as interval numbers and applied functional parametric form in the proposed prey-predator system. The positivity and boundedness of the model are checked, and a stability analysis of the five equilibrium points is performed. Numerical simulations are performed to study the effect of the interval number and to illustrate analytical studies.

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“…They all studied a predator-prey model with fuzzy initial conditions. Fuzzy predator-prey models with functional responses have also been studied by Pal et al [27], Yu et al [28], Pal et al [29], Meng and Wu [30], Mahata et al [31], and Pal et al [32], who presented fuzzy predator-prey harvesting models. Their work studied two species of predator-prey harvesting models by considering fuzzy parameters.…”

Section: Introductionmentioning

confidence: 99%

A Runge-Kutta numerical scheme applied in solving predator-prey fuzzy model with Holling type II functional response

Sukarsih

Supriatna

Carnia

et al. 2023

Front. Appl. Math. Stat.

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The predator-prey model has been extensively studied, but only studies models in a certain environment, where all parameters and initial values involved in the model are assumed to be certain. In real practice, some parameters and initial values are often uncertain. To overcome this uncertainty problem, a model can be made by using a fuzzy theoretical approach. In this paper, we develop a numerical scheme for solving two predator-prey models with a Holling type II functional response by considering fuzzy parameters and initial populations. The behavior of the model was studied qualitatively using the 5th order Runge-Kutta method of which was modified for the fuzzy system using the Zadeh extension principle. The numerical simulation results show that, when the initial populations of prey and predators are fuzzy, the behavior of the fuzzy model would be qualitatively the same as the crisp model. Finally, we conclude that the resulting fuzzy behavior represents a generalization of crisp behavior. This gives more realistic results since the solution is obtained by explicitly considering the problem of uncertainty.

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Study of two species prey-predator model in imprecise environment with MSY policy under different harvesting scenario

Cited by 16 publications

References 49 publications

Bipolar complex fuzzy submodules

Bipolar complex fuzzy submodules

A three-component prey-predator system with interval number

A Runge-Kutta numerical scheme applied in solving predator-prey fuzzy model with Holling type II functional response

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