Research article

Computational modeling of financial crime population dynamics under different fractional operators

  • Received: 17 January 2023 Revised: 19 June 2023 Accepted: 20 June 2023 Published: 29 June 2023
  • MSC : 34A08, 49J15, 65P99

  • This paper presents an analysis and numerical simulation of financial crime population dynamics using fractional order calculus and Newton's polynomial. The dynamics of financial crimes are modeled as a fractional-order system, which is then solved using numerical methods based on Newton's polynomial. The results of the simulation provide insights into the behavior of financial crime populations over time, including the stability and convergence of the systems. The study provides a new approach to understanding financial crime populations and has potential applications in developing effective strategies for combating financial crimes. Fractional derivatives are commonly applied in many interdisciplinary fields of science because of its effectiveness in understanding and analyzing complicated phenomena. In this work, a mathematical model for the population dynamics of financial crime with fractional derivatives is reformulated and analyzed. A fractional-order financial crime model using the new Atangana-Baleanu-Caputo (ABC) derivative is introduced. The reproduction number for financial crime is calculated. In addition, the relative significance of model parameters is also determined by sensitivity analysis. The existence and uniqueness of the solution in consideration of the ABC derivative are discussed. A number of conditions are established for the existence and Ulam-Hyers stability of financial crime equilibria. A numerical scheme is presented for the proposed model, starting with the Caputo-Fabrizio fractional derivative, followed by the Caputo and Atangana-Baleanu fractional derivatives. Finally, we solve the models with fractal-fractional derivatives.

    Citation: Rahat Zarin, Abdur Raouf, Amir Khan, Aeshah A. Raezah, Usa Wannasingha Humphries. Computational modeling of financial crime population dynamics under different fractional operators[J]. AIMS Mathematics, 2023, 8(9): 20755-20789. doi: 10.3934/math.20231058

    Related Papers:

  • This paper presents an analysis and numerical simulation of financial crime population dynamics using fractional order calculus and Newton's polynomial. The dynamics of financial crimes are modeled as a fractional-order system, which is then solved using numerical methods based on Newton's polynomial. The results of the simulation provide insights into the behavior of financial crime populations over time, including the stability and convergence of the systems. The study provides a new approach to understanding financial crime populations and has potential applications in developing effective strategies for combating financial crimes. Fractional derivatives are commonly applied in many interdisciplinary fields of science because of its effectiveness in understanding and analyzing complicated phenomena. In this work, a mathematical model for the population dynamics of financial crime with fractional derivatives is reformulated and analyzed. A fractional-order financial crime model using the new Atangana-Baleanu-Caputo (ABC) derivative is introduced. The reproduction number for financial crime is calculated. In addition, the relative significance of model parameters is also determined by sensitivity analysis. The existence and uniqueness of the solution in consideration of the ABC derivative are discussed. A number of conditions are established for the existence and Ulam-Hyers stability of financial crime equilibria. A numerical scheme is presented for the proposed model, starting with the Caputo-Fabrizio fractional derivative, followed by the Caputo and Atangana-Baleanu fractional derivatives. Finally, we solve the models with fractal-fractional derivatives.



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    [1] P. Gottschalk, Categories of financial crime, Journal of Financial Crime, 17 (2010), 441–458. https://doi.org/10.1108/13590791011082797 doi: 10.1108/13590791011082797
    [2] K. H. S. Pickett, J. M. Pickett, Financial crime investigation and control, John Wiley & Sons, 2002.
    [3] H. R. Thieme, Mathematics in population biology, Princeton University Press, 2018.
    [4] J. O. Akanni, F. O. Akinpelu, S. Olaniyi, A. T. Oladipo, A. W. Ogunsola, Modelling financial crime population dynamics: optimal control and cost-effectiveness analysis, Int. J. Dynam. Control, 8 (2020), 531–544. https://doi.org/10.1007/s40435-019-00572-3 doi: 10.1007/s40435-019-00572-3
    [5] H. Zhao, Z. Feng, C. Castillo-Chavez, The dynamics of poverty and crime, (Chinese), Journal of Shanghai Normal University (Natural Sciences Mathematics), 43 (2014), 486–495. https://doi.org/10.3969/J.1SSN.100-5137.2014.05.005 doi: 10.3969/J.1SSN.100-5137.2014.05.005
    [6] J. C. Nuño, M. A. Herrero, M. Primicerio, A triangle model of criminality, Physica A, 387 (2008), 2926–2936. https://doi.org/10.1016/j.physa.2008.01.076 doi: 10.1016/j.physa.2008.01.076
    [7] J. C. Nuño, M. A. Herrero, M. Primicerio, Fighting cheaters: How and how much to invest, Eur. J. Appl. Math., 21 (2010), 459–478. https://doi.org/10.1017/S0956792510000094 doi: 10.1017/S0956792510000094
    [8] J. B. Shukla, A. Goyal, K. Agrawal, H. Kushwah, A. Shukla, Role of technology in combating social crimes: a modeling study, Eur. J. Appl. Math., 24 (2013), 501–514. https://doi.org/10.1017/S0956792513000065 doi: 10.1017/S0956792513000065
    [9] D. McMillon, C. P. Simon, J. Morenoff, Modeling the underlying dynamics of the spread of crime, PLoS ONE, 9 (2014), e88923. https://doi.org/10.1371/journal.pone.0088923 doi: 10.1371/journal.pone.0088923
    [10] G. González-Parra, B. Chen-Charpentier, H. V. Kojouharov, Mathematical modeling of crime as a social epidemic, J. Interdiscip. Math., 21 (2018), 623–643. https://doi.org/10.1080/09720502.2015.1132574 doi: 10.1080/09720502.2015.1132574
    [11] A. K. Srivastav, M. Ghosh, P. Chandra, Modeling dynamics of the spread of crime in a society, Stoch. Anal. Appl., 37 (2019), 991–1011. https://doi.org/10.1080/07362994.2019.1636658 doi: 10.1080/07362994.2019.1636658
    [12] O. M. Ibrahim, D. Okuonghae, M. N. O. Ikhile, Mathematical modeling of the population dynamics of age-structured criminal gangs with correctional intervention measures, Appl. Math. Model., 107 (2022), 39–71. https://doi.org/10.30511/mcs.2022.255061 doi: 10.30511/mcs.2022.255061
    [13] S. Athithan, M. Ghosh, X.-Z. Li, Mathematical modeling and optimal control of corruption dynamics, Asian-Eur. J. Math., 11 (2018), 1850090. https://doi.org/10.1142/S1793557118500900 doi: 10.1142/S1793557118500900
    [14] U. A. M. Roslan, S. Zakaria, A. Alias, S. M. A. Malik, A mathematical model on the dynamics of poverty, poor and crime in west malaysia, Far East Journal of Mathematical Sciences, 107 (2018), 309–319. http://doi.org/10.17654/MS107020309 doi: 10.17654/MS107020309
    [15] F. S. Chaharborj, B. Pourghahramani, S. S. Chaharborj, A dynamic economic model of criminal activity in the criminal law, International Journal of Basic Applied Sciences, 6 (2017), 73–76. https://doi.org/10.14419/ijbas.v6i4.7969 doi: 10.14419/ijbas.v6i4.7969
    [16] F. Nyabadza, C. P. Ogbogbo, J. Mushanyu, Modelling the role of correctional services on gangs: insights through a mathematical model, R. Soc. Open Sci., 4 (2017), 170511. https://doi.org/10.1098/rsos.170511 doi: 10.1098/rsos.170511
    [17] J. Sooknanan, B. Bhatt, D. M. G. Comissiong, A modified predator-prey model for the interaction of police and gangs, R. Soc. Open Sci., 3 (2016), 160083. https://doi.org/10.1098/rsos.160083 doi: 10.1098/rsos.160083
    [18] R. Manasevich, Q. H. Phan, P. Souplet, Global existence of solutions for a chemotaxis-type system arising in crime modelling, Eur. J. Appl. Math., 24 (2013), 273–296. http://doi.org/10.1017/S095679251200040X doi: 10.1017/S095679251200040X
    [19] M. Goyal, H. M. Baskonus, A. Prakash, An efficient technique for a time fractional model of lassa hemorrhagic fever spreading in pregnant women, Eur. Phys. J. Plus, 134 (2019), 482. https://doi.org/10.1140/epjp/i2019-12854-0 doi: 10.1140/epjp/i2019-12854-0
    [20] W. Gao, P. Veeresha, D. G. Prakasha, H. M. Baskonus, G. Yel, New approach for the model describing the deathly disease in pregnant women using Mittag-Leffler function, Chaos Soliton. Fract., 134 (2020), 109696. https://doi.org/10.1016/j.chaos.2020.109696 doi: 10.1016/j.chaos.2020.109696
    [21] R. T. Alqahtani, S. Ahmad, A. Akgül, Dynamical analysis of bio-ethanol production model under generalized nonlocal operator in Caputo sense, Mathematics, 9 (2021), 2370. https://doi.org/10.3390/math9192370 doi: 10.3390/math9192370
    [22] P. Agarwal, R. Singh, Modelling of transmission dynamics of Nipah virus (Niv): a fractional order approach, Physica A, 547 (2020), 124243. http://doi.org/10.1016/j.physa.2020.124243 doi: 10.1016/j.physa.2020.124243
    [23] R. Zarin, A. Khan, A. Yusuf, S. Abdel-Khalek, M. Inc, Analysis of fractional COVID-19 epidemic model under Caputo operator, Math. Method. Appl. Sci., 46 (2023), 7944–7964. https://doi.org/10.1002/mma.7294 doi: 10.1002/mma.7294
    [24] R. Zarin, A. Khan, P. Kumar, U. W. Humphries, Fractional-order dynamics of Chagas-HIV epidemic model with different fractional operators, AIMS Mathematics, 7 (2022), 18897–18924. https://doi.org/10.3934/math.20221041 doi: 10.3934/math.20221041
    [25] P. Agarwal, J. Choi, R. B. Paris, Extended Riemann-Liouville fractional derivative operator and its applications, J. Nonlinear Sci. Appl., 8 (2015), 451–466. http://doi.org/10.22436/jnsa.008.05.01 doi: 10.22436/jnsa.008.05.01
    [26] R. Zarin, A. Khan, M. Inc, U. W. Humphries, T. Karite, Dynamics of five grade leishmania epidemic model using fractional operator with Mittag–Leffler kernel, Chaos Soliton. Fract., 147 (2021), 110985. https://doi.org/10.1016/j.chaos.2021.110985 doi: 10.1016/j.chaos.2021.110985
    [27] H. M. Srivastava, W. Adel, M. Izadi, A. A. El-Sayed, Solving some physics problems involving fractional-order differential equations with the Morgan-Voyce polynomials, Fractal Fract., 7 (2023), 301. https://doi.org/10.3390/fractalfract7040301 doi: 10.3390/fractalfract7040301
    [28] W. Weera, T. Botmart, C. Chantawat, Z. Sabir, W. Adel, M. A. Z. Raja, et al., An intelligence computational approach for the fractional 4D chaotic financial model, Comput. Mater. Con., 74 (2023), 2711–2724. http://doi.org/10.32604/cmc.2023.033233 doi: 10.32604/cmc.2023.033233
    [29] A. El-Mesady, A. Elsonbaty, W. Adel, On nonlinear dynamics of a fractional order monkeypox virus model, Chaos Soliton. Fract., 164 (2022), 112716. https://doi.org/10.1016/j.chaos.2022.112716 doi: 10.1016/j.chaos.2022.112716
    [30] R. Zarin, Modeling and numerical analysis of fractional order hepatitis B virus model with harmonic mean type incidence rate, Comput. Method. Biomech. Biomed. Eng., in press. https://doi.org/10.1080/10255842.2022.2103371
    [31] A. Khan, H. Khan, J. F. Gómez-Aguilar, T. Abdeljawad, Existence and Hyers-Ulam stability for a nonlinear singular fractional differential equations with Mittag-Leffler kernel, Chaos Soliton. Fract., 127 (2019), 422–427. https://doi.org/10.1016/j.chaos.2019.07.026 doi: 10.1016/j.chaos.2019.07.026
    [32] X. Jiang, J. Li, B. Li, W. Yin, L. Sun, X. Chen, Bifurcation, chaos, and circuit realisation of a new four-dimensional memristor system, Int. J. Nonlinear Sci. Numer. Simulat., in press. https://doi.org/10.1515/ijnsns-2021-0393
    [33] B. Li, Z. Eskandari, Z. Avazzadeh, Dynamical behaviors of an SIR epidemic model with discrete time, Fractal Fract., 6 (2022), 659. https://doi.org/10.3390/fractalfract6110659 doi: 10.3390/fractalfract6110659
    [34] A. Khan, J. F. Gómez-Aguilar, T. S. Khan, H. Khan, Stability analysis and numerical solutions of fractional order HIV/AIDS model, Chaos Soliton. Fract., 122 (2019), 119–128. https://doi.org/10.1016/j.chaos.2019.03.022 doi: 10.1016/j.chaos.2019.03.022
    [35] Y. Wang, S. Liu, A. Khan, On fractional coupled logistic maps: Chaos analysis and fractal control, Nonlinear Dyn., 111 (2023), 5889–5904. http://doi.org/10.1007/s11071-022-08141-8 doi: 10.1007/s11071-022-08141-8
    [36] A. Khan, K. Shah, T. Abdeljawad, M. Sher, On fractional order Sine-Gordon equation involving nonsingular derivative, Fractals, in press. https://doi.org/10.1142/S0218348X23400078
    [37] P. Liu, A. Din, R. Zarin, Numerical dynamics and fractional modeling of hepatitis B virus model with non-singular and non-local kernels, Results Phys., 39 (2022), 105757. https://doi.org/10.1016/j.rinp.2022.105757 doi: 10.1016/j.rinp.2022.105757
    [38] R. Zarin, H. Khaliq, A. Khan, D. Khan, A. Akgül, U. W. Humphries, Deterministic and fractional modeling of a computer virus propagation, Results Phys., 33 (2022), 105130. https://doi.org/10.1016/j.rinp.2021.105130 doi: 10.1016/j.rinp.2021.105130
    [39] K. Bansal, S. Arora, K. S. Pritam, T. Mathur, S. Agarwal, Dynamics of crime transmission using fractional-order differential equations, Fractals, 30 (2022), 2250012. https://doi.org/10.1142/S0218348X22500128 doi: 10.1142/S0218348X22500128
    [40] K. S. Pritam, Sugandha, T. Mathur, S. Agarwal, Underlying dynamics of crime transmission with memory, Chaos Soliton. Fract., 146 (2021), 110838. https://doi.org/10.1016/j.chaos.2021.110838 doi: 10.1016/j.chaos.2021.110838
    [41] M. Partohaghighi, V. Kumar, A. Akgül, Comparative study of the fractional-order crime system as a social epidemic of the USA scenario, Int. J. Appl. Comput. Math., 8 (2022), 190. https://doi.org/10.1007/s40819-022-01399-x doi: 10.1007/s40819-022-01399-x
    [42] M. u. Rahman, S. Ahmad, M. Arfan, A. Akgül, F. Jarad, Fractional order mathematical model of serial killing with different choices of control strategy, Fractal Fract., 6 (2022), 162. https://doi.org/10.3390/fractalfract6030162 doi: 10.3390/fractalfract6030162
    [43] A. Atangana, S. İğret Araz, A novel Covid-19 model with fractional differential operators with singular and non-singular kernels: analysis and numerical scheme based on Newton polynomial, Alex. Eng. J., 60 (2021), 3781–3806. https://doi.org/10.1016/j.aej.2021.02.016 doi: 10.1016/j.aej.2021.02.016
    [44] H. W. Hethcote, The mathematics of infectious diseases, SIAM Rev., 42 (2000), 599–653. https://doi.org/10.1137/S0036144500371907 doi: 10.1137/S0036144500371907
    [45] P. van den Driessche, J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math. Biosci., 180 (2002), 29–48. https://doi.org/10.1016/S0025-5564(02)00108-6 doi: 10.1016/S0025-5564(02)00108-6
    [46] R. Mahardika, Widowati, Y. D. Sumanto, Routh-hurwitz criterion and bifurcation method for stability analysis of tuberculosis transmission model, J. Phys.: Conf. Ser., 1217 (2019), 012056. https://doi.org/10.1088/1742-6596/1217/1/012056 doi: 10.1088/1742-6596/1217/1/012056
    [47] A. Hoare, D. G. Regan, D. P. Wilson, Sampling and sensitivity analyses tools (SaSAT) for computational modelling, Theor. Biol. Med. Model., 5 (2008), 4. https://doi.org/10.1186/1742-4682-5-4 doi: 10.1186/1742-4682-5-4
    [48] J. Ding, A. Al dmour, Abnormal behavior of fractional differential equations in processing computer big data, Applied Mathematics and Nonlinear Sciences, 8 (2023), 291–298. https://doi.org/10.2478/amns.2022.2.00011 doi: 10.2478/amns.2022.2.00011
    [49] D. Zhang, L. Yang, A. Arbab, The uniqueness of solutions of fractional differential equations in university mathematics teaching based on the principle of compression mapping, Applied Mathematics and Nonlinear Sciences, 8 (2023), 331–338. https://doi.org/10.2478/amns.2022.2.00014 doi: 10.2478/amns.2022.2.00014
    [50] Y. Chen, Z. Chang, H. Mohamed, Mathematical modeling thoughts and methods based on fractional differential equations in teaching, Applied Mathematics and Nonlinear Sciences, 8 (2023), 299–308. https://doi.org/10.2478/amns.2022.2.00012 doi: 10.2478/amns.2022.2.00012
    [51] Q. Zhao, Optimal model combination of cross-border E-commerce platform operation based on fractional differential equations, Applied Mathematics and Nonlinear Sciences, 8 (2023), 517–526. https://doi.org/10.2478/amns.2022.2.0036 doi: 10.2478/amns.2022.2.0036
    [52] F. Wang, X. Xue, X. Zhu, A. S. Shatat, Fractional differential equations in the standard construction model of the educational application of the internet of things, Applied Mathematics and Nonlinear Sciences, 8 (2023), 527–534. https://doi.org/10.2478/amns.2022.2.0037 doi: 10.2478/amns.2022.2.0037
    [53] A. Khan, R. Zarin, S. Khan, A. Saeed, T. Gul, U. W. Humphries, Fractional dynamics and stability analysis of COVID-19 pandemic model under the harmonic mean type incidence rate, Comput. Method. Biomech. Biomed. Eng., 25 (2022), 619–640. https://doi.org/10.1080/10255842.2021.1972096 doi: 10.1080/10255842.2021.1972096
    [54] A. Khan, R. Zarin, U. W. Humphries, A. Akgül, A. Saeed, T. Gul, Fractional optimal control of COVID-19 pandemic model with generalized Mittag-Leffler function, Adv. Differ. Equ., 2021 (2021), 387. https://doi.org/10.1186/s13662-021-03546-y doi: 10.1186/s13662-021-03546-y
    [55] A. Atangana, D. Baleanu, New fractional derivatives with nonlocal and non-singular kernel: theory and application to heat transfer model, arXiv: 1602.03408.
    [56] A. Atangana, S. İğret Araz, New numerical scheme with Newton polynomial: theory, methods, and applications, Academic Press, 2021. https://doi.org/10.1016/C2020-0-02711-8
    [57] A. Atangana, S. İğret Araz, Mathematical model of COVID-19 spread in Turkey and South Africa: theory, methods, and applications, Adv. Differ. Equ., 2020 (2020), 659. https://doi.org/10.1186/s13662-020-03095-w doi: 10.1186/s13662-020-03095-w
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