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Parameter Estimation of Fractional Gompertz Model Using Cuckoo Search Algorithm

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Fractional Derivatives with Mittag-Leffler Kernel

Abstract

In this chapter, a meta-heuristic optimization algorithm, called cuckoo search algorithm is applied to determine the optimal parameters of the fractional Gompertz model via Liouville–Caputo and Atangana–Baleanu–Caputo fractional derivatives. The numerical solutions of the proposed models were obtained using the Adams method. The proposed methodology is tested on epidemiological examples. In the interval considered, the fractional models had the best fit for the epidemiological data considered. The effectiveness of the methodology is shown by a comparison with the classical models. A comparison between the fractional models and the classical models was carried out to show the effectiveness of our methodology.

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References

  1. Gompertz, B.: On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philos. Trans. R. Soc. Lond. B Biol. Sci. 182, 513–585 (1825)

    Google Scholar 

  2. Chatterjee, T., Chatterjee, B.K., Majumdar, D., Chakrabarti, P.: Antibacterial effect of silver nanoparticles and the modeling of bacterial growth kinetics using a modified Gompertz model. Biochim. Biophys. ca (BBA)-Gen. Subj. 1850(2), 299–306 (2015)

    Article  Google Scholar 

  3. Budiyono, I., Sumardiono, S.: Kinetic model of biogas yield production from vinasse at various initial pH: comparison between modified Gompertz model and first order kinetic model. Res. J. Appl. Sci. Eng. Technol. 7(13), 2798–2805 (2014)

    Article  Google Scholar 

  4. Tjorve, K.M., Tjorve, E.: The use of Gompertz models in growth analyses, and new Gompertz-model approach: an addition to the Unified-Richards family. PloS one 12(6), 1–9 (2017)

    Article  MATH  Google Scholar 

  5. Liu, H., Chen, N., Feng, C., Tong, S., Li, R.: Impact of electro-stimulation on denitrifying bacterial growth and analysis of bacterial growth kinetics using a modified Gompertz model in a bio-electrochemical denitrification reactor. Bioresour. Technol. 232, 344–353 (2017)

    Article  Google Scholar 

  6. Costa, B.A., Lemos, J.M.: Drug administration design for cancer Gompertz model based on the Lyapunov method. In: Controlo 2016, vol. 1, pp. 131–141. Springer International Publishing, Berlin (2017)

    Google Scholar 

  7. Horiuchi, S., Ouellette, N., Cheung, S.L.K., Robine, J.M.: Modal age at death: lifespan indicator in the era of longevity extension. Vienna Yearb. Popul. Res. 1, 37–69 (2013)

    Google Scholar 

  8. Izquierdo, F., Prats, C., López, D.: The use of the Gompertz model in its differential form for weed emergence modelling. In: XV Congreso de la Sociedad Española de Malherbología, SEMh, 2015, vol. 1, pp. 367–373 (2015)

    Google Scholar 

  9. Ryan, C.A., Billington, S.L., Criddle, C.S.: Assessment of models for anaerobic biodegradation of a model bioplastic: poly (hydroxybutyrate-co-hydroxyvalerate). Bioresour. Technol. 227, 205–213 (2017)

    Article  Google Scholar 

  10. Mohammadi Farrokhran, E., Mahmoodi, M., Mohammad, K., Rahimi, A., Majlesi, F., Parsaeian, M.: Study of factors affecting first birth interval using modified Gompertz cure model in west Azarbaijan province, Iran. Iran. J. Epidemiol. 9(1), 41–51 (2013)

    Google Scholar 

  11. Du, M., Wang, Z., Hu, H.: Measuring memory with the order of fractional derivative. Sci. Rep. 3(1), 1–3 (2013)

    Google Scholar 

  12. Magin, R.L.: Fractional calculus models of complex dynamics in biological tissues. Comput. Math. Appl. 59(5), 1586–1593 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  13. Atici, F.M., Şengul, S.: Modeling with fractional difference equations. J. Math. Anal. Appl. 369(1), 1–9 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  14. Bolton, L., Cloot, A.H., Schoombie, S.W., Slabbert, J.P.: A proposed fractional-order Gompertz model and its application to tumour growth data. Math. Med. Biol. J. IMA 32(2), 187–207 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  15. Atangana, A., Secer, A.: A note on fractional order derivatives and table of fractional derivatives of some special functions. Abstr. Appl. Anal. 2013, 1–15 (2013)

    MathSciNet  MATH  Google Scholar 

  16. Caputo, M., Fabrizio, M.: A new definition of fractional derivative without singular kernel. Prog. Fract. Differ. Appl. 1(2), 73–85 (2015)

    Google Scholar 

  17. Atangana, A., Baleanu, D.: New fractional derivatives with nonlocal and non-singular kernel. Theory and application to heat transfer model. Therm. Sci. 20(2), 763–769 (2016)

    Article  Google Scholar 

  18. Yang, X.S., Deb, S.: Cuckoo search: recent advances and applications. Neural Comput. Appl. 24(1), 169–174 (2014)

    Article  Google Scholar 

  19. Abdel-Basset, M., Hessin, A.N., Abdel-Fatah, L.: A comprehensive study of cuckoo-inspired algorithms. Neural Comput. Appl. 1, 1–17 (2016)

    Google Scholar 

  20. Yang, X.S., Deb, S.: Engineering optimisation by cuckoo search. Int. J. Math. Model. Numer. Optim. 1(4), 330–343 (2010)

    MATH  Google Scholar 

  21. Changpin, L., Chunxing, T.: On the fractional Adams method. Comput. Math. Appl. 58(8), 1573–1588 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  22. Diethelm, K., Ford, N.J., Freed, A.D.: Detailed error analysis for a fractional Adams method. Numer. Algorithms 36(1), 31–52 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  23. Alkahtani, B.S.T.: Chua’s circuit model with Atangana–Baleanu derivative with fractional order. Chaos Solitons Fractals 89, 1–5 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  24. Wu, J.W., Hung, W.L., Tsai, C.H.: Estimation of parameters of the Gompertz distribution using the least squares method. Appl. Math. Comput. 158(1), 133–147 (2004)

    MathSciNet  MATH  Google Scholar 

  25. Fekedulegn, D., Mac Siurtain, M.P., Colbert, J.J.: Parameter estimation of nonlinear growth models in forestry. Silva Fenn. 33(4), 327–336 (1999)

    Article  Google Scholar 

  26. Lewis, C.D.: Industrial and Business Forecasting Methods: A Practical Guide to Exponential Smoothing and Curve Fitting. Butterworth-Heinemann, Oxford (1982)

    Google Scholar 

  27. https://knoema.com/UNAIDSS2016/united-nations-aids-statistics-2016

  28. https://knoema.com/WZVO2016jul/world-zika-virus-epidemic-2015-16-monthly-update

  29. https://knoema.com/hlth-ps-scre/breast-cancer-and-cervical-cancer-screenings

  30. https://knoema.com/hlth-co-ren/end-stage-renal-failure-esrf-patients

  31. https://knoema.com/WBHNPStats2016May/health-nutrition-and-population-statistics-world-bank

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Acknowledgements

Jesús Emmanuel Solís Pérez acknowledges the support provided by CONACyT through the assignment doctoral fellowship. José Francisco Gómez Aguilar acknowledges the support provided by CONACyT: Cátedras CONACyT para jóvenes investigadores 2014. José Francisco Gómez Aguilar and Ricardo Fabricio Escobar Jiménez acknowledges the support provided by SNI-CONACyT.

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Correspondence to J. F. Gómez-Aguilar .

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Solís-Pérez, J.E., Gómez-Aguilar, J.F., Escobar-Jiménez, R.F., Torres, L., Olivares-Peregrino, V.H. (2019). Parameter Estimation of Fractional Gompertz Model Using Cuckoo Search Algorithm. In: Gómez, J., Torres, L., Escobar, R. (eds) Fractional Derivatives with Mittag-Leffler Kernel. Studies in Systems, Decision and Control, vol 194. Springer, Cham. https://doi.org/10.1007/978-3-030-11662-0_6

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  • DOI: https://doi.org/10.1007/978-3-030-11662-0_6

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