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Research Article

Covid-19 data modelling using hybrid conjugate gradient method

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Pages 837-853 | Received 01 Jun 2021, Published online: 11 Aug 2022

References

  • P. Mtagulwa and P. Kaelo, “A Convergent Modified HS-DY Hybrid Conjugate Gradient Method for Unconstrained Optimization Problems,” Journal of Information and Optimization Sciences, vol. 40, no. 1, pp. 97-113, 2019, DOI: 10.1080/02522667.2018.1424087.
  • V. Singh, R. C. Poonia, S. K. P. Dass, P. A. V. Bhatnagar and L. Raja, “Prediction Of COVID-19 Corona Virus Pandemic Based on Time Series Data Using Support Vector Machine,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 23, no. 8, pp. 1583-1597, 2020, DOI: 10.1080/09720529.2020.1784535.
  • V. B. R. C. Poonia, P. Nagar, S. Kumar, V. Singh, L. Raja and P. Dass, “Descriptive Analysis of COVID-19 Patients in The Context of India,” Journal of Interdisciplinary Mathematics, vol. 24, no. 3, pp. 489-504, 2021, DOI: 10.1080/09720502.2020.176163.
  • A. Abashar, M. Mamat, M. Rivaie, I. Mohd, and O. Omer, “The proof of sufficient descent condition for a new type of conjugate gradient methods,” in AIP Conference Proceedings, 2014, vol. 1602, no. 1: American Institute of Physics, pp. 296-303.
  • M. R. Hestenes and E. Stiefel, Methods of conjugate gradients for solving linear systems (no. 1). NBS Washington, DC, 1952.
  • Y.-H. Dai and Y. Yuan, “A nonlinear conjugate gradient method with a strong global convergence property,” SIAM Journal on optimization, vol. 10, no. 1, pp. 177-182, 1999.
  • E. Polak and G. Ribiere, “Note sur la convergence de méthodes de directions conjuguées,” ESAIM: Mathematical Modelling and Numerical Analysis-Modélisation Mathématique et Analyse Numérique, vol. 3, no. R1, pp. 35-43, 1969.
  • N. H. A. Ghani, M. Rivaie, and M. Mamat, “A modified form of conjugate gradient method for unconstrained optimization problems,” in AIP Conference proceedings, 2016, vol. 1739, no. 1: AIP Publishing LLC, p. 020076.
  • N. Zull, N. Aini, M. Rivaie, and M. Mamat, “A new gradient method for solving linear regression model,” International Journal of Recent Technology and Engineering, vol. 7, no. 5, pp. 624-630, 2019.
  • L. Wang, M. Cao, F. Xing, and Y. Yang, “The new spectral conjugate gradient method for large-scale unconstrained optimisation,” Journal of Inequalities and Applications, vol. 2020, no. 1, pp. 1-11, 2020.
  • N. Zull, M. Rivaie, M. Mamat, Z. Salleh, and Z. Amani, “Global convergence of a new spectral conjugate gradient by using strong wolfe line search,” Applied Mathematical Sciences, vol. 9, no. 63, pp. 3105-3117, 2015.
  • J. Liu and S. Du, “Modified three-term conjugate gradient method and its applications,” Mathematical Problems in Engineering, vol. 2019, 2019.
  • J. Liu, Y. Zhao, and X. Wu, “Some three-term conjugate gradient methods with the new direction structure,” Applied Numerical Mathematics, vol. 150, pp. 433-443, 2020.
  • D. Touati-Ahmed and C. Storey, “Efficient hybrid conjugate gradient techniques,” Journal of optimization theory and applications, vol. 64, no. 2, pp. 379-397, 1990.
  • Y. Hu and C. Storey, “Global convergence result for conjugate gradient methods,” Journal of Optimization Theory and Applications, vol. 71, no. 2, pp. 399-405, 1991.
  • N. Ghani, N. Mohamed, N. Zull, S. Shoid, M. Rivaie, and M. Mamat, “Performance comparison of a new hybrid conjugate gradient method under exact and inexact line searches,” in Journal of Physics: Conference Series, 2017, vol. 890, no. 1: IOP Publishing, pp. 012106.
  • S. Shoid, N. Zull, M. Rivaie, M. Mamat, P. Liza Ghazali, and M. Afendee Mohamed, “A New Hybrid of Conjugate Gradient Method with Descent Properties,” International Journal of Engineering Technology, vol. 7, no. 3.28, pp. 354-357, 2018, DOI: 10.14419/ijet.v7i3.28.27385.
  • S. S. Djordjevic, “New Hybrid Conjugate Gradient Method as A Convex Combination of HS and FR Methods,” Editorial Board Members, 2018.
  • X. Yang, Z. Luo, and X. Dai, “A Global Convergence of LS-CD Hybrid Conjugate Gradient Method,” Adv. Numerical Analysis, vol. 2013, pp. 517452:1-517452:5, 2013.
  • O. J. Adeleke, M. O. Olusanya, and I. A. Osinuga, “A PRP-HS Type Hybrid Nonlinear Conjugate Gradient Method for Solving Unconstrained Optimization Problems,” in Proceedings of the Computational Methods in Systems and Software, 2019: Springer, pp. 58-68.
  • A. B. Abubakar, P. Kumam, M. Malik, P. Chaipunya, and A. H. Ibrahim, “A hybrid FR-DY conjugate gradient algorithm for unconstrained optimization with application in portfolio selection,” AIMS Mathematics, vol. 6, no. 6, pp. 6506-6527, 2021.
  • M. Li, “A modified Hestense–Stiefel conjugate gradient method close to the memoryless BFGS quasi-Newton method,” Optimization Methods and Software, vol. 33, no. 2, pp. 336-353, 2018.
  • M. Li, “A three term polak-ribière-polyak conjugate gradient method close to the memoryless BFGS quasi-Newton method,” Journal of Industrial & Management Optimization, vol. 16, no. 1, pp. 245, 2020.
  • M. Malik, M. Mamat, S. S. Abas, and I. M. Sulaiman, “Performance Analysis of New Spectral and Hybrid Conjugate Gradient Methods for Solving Unconstrained Optimization Problems,” IAENG International Journal of Computer Science, vol. 48, no. 1, 2021.
  • M. Rivaie, M. Mamat, L. W. June, and I. Mohd, “A new class of nonlinear conjugate gradient coefficients with global convergence properties,” Applied Mathematics and Computation, vol. 218, no. 22, pp. 11323-11332, 2012.
  • I. Sulaiman, M. Mamat, M. Waziri, U. Yakubu, and M. Malik, “The performance analysis of a new modification of conjugate gradient parameter for unconstrained optimization models,” Mathematics and Statistics, vol. 9, no. 1, pp. 16-23, 2021.
  • M. Rivaie, M. Mamat, and A. Abashar, “A new class of nonlinear conjugate gradient coefficients with exact and inexact line searches,” Applied Mathematics and Computation, vol. 268, pp. 1152-1163, 2015.
  • Z. Dai, “Comments on a new class of nonlinear conjugate gradient coefficients with global convergence properties,” Applied Mathematics and Computation, vol. 276, pp. 297-300, 2016.
  • I. Sulaiman, M. Mamat, M. Waziri, U. Yakubu, and M. Malik, “The convergence properties of a new hybrid conjugate gradient parameter for unconstrained optimization models,” in Journal of Physics: Conference Series, 2021, vol. 1734, no. 1: IOP Publishing, p. 012012.
  • F. N. Al-Namat and G. M. Al-Naemi, “Global Convergence Property with Inexact Line Search for a New Hybrid Conjugate Gradient Method,” Open Access Library Journal, vol. 7, no. 2, pp. 1-14, 2020.
  • M. Malik, S. S. Abas, M. Mamat, and I. S. Mohammed, “A new hybrid conjugate gradient method with global convergence properties,” International Journal of Advanced Science and Technology, vol. 29, no. 5, pp. 199-210, 2020.
  • M. Mamat, M. Rivaie, I. Mohd, and M. Fauzi, “A new conjugate gradient coefficient for unconstrained optimization,” Int. J. Contemp. Math. Sciences, vol. 5, no. 29, pp. 1429-1437, 2010.
  • G. Zoutendijk, “Nonlinear programming, computational methods,” Integer and nonlinear programming, pp. 37-86, 1970.
  • N. Zull, S. Shoid, N. Ghani, N. Mohamed, M. Rivaie, and M. Mamat, “A conjugate gradient method with descent properties under strong Wolfe line search,” in Journal of Physics: Conference Series, 2017, vol. 890, no. 1: IOP Publishing, p. 012105.
  • N. Andrei, “An unconstrained optimization test functions collection,” Adv. Model. Optim, vol. 10, no. 1, pp. 147-161, 2008.
  • E. D. Dolan and J. J. Moré, “Benchmarking optimization software with performance profiles,” Mathematical programming, vol. 91, no. 2, pp. 201-213, 2002.
  • N. Aini, N. Hajar, M. Mamat, N. Zull, and M. Rivaie, “Hybrid quasi-newton and conjugate gradient method for solving unconstrained optimization problems,” Journal of Engineering and Applied Sciences, vol. 12, no. 18, pp. 4627-4631, 2017.
  • http;//covid-19.moh.gov.my/
  • H. Motulsky and A. Christopoulos, Fitting models to biological data using linear and nonlinear regression: a practical guide to curve fitting. Oxford University Press, 2004.
  • H. Abdi, “The method of least squares,” Encyclopedia of measurement and statistics, vol. 1, pp. 530-532, 2007.

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