[1] A. Aliyari Boroujeni, R. Pourgholi, and S.H. Tabasi, A new improved teaching‑learning‑based optimization (ITLBO) algorithm for solving nonlinear inverse partial differential equation problems, Comp. Appl. Math. 42 (2023), 99.
[2] A. Aliyari Boroujeni, R. Pourgholi, and S.H. Tabasi, Solving inverse partial differential equations problems by using teaching learning based optimization algorithm, TWMS J. Appl. Eng. Math. (2024).
[3] A. Aliyari Boroujeni, R. Pourgholi, and S.H. Tabasi, Numerical solutions of KDV and mKDV equations: Using sequence and multi‑core parallelization implementation, J. Comput. Appl. Math. 454 (2025), 116184.
[4] R.S. Anderssen, Inverse problems: a pragmatist's approach to the recovery of information from indirect measurements, Aust. N. Z. Ind. Appl. Math. J. 46 (2005), C588‑C622.
[5] D.G. Aronson and H.F. Weinberger, Multidimensional nonlinear diffusion arising in population genetics, Adv. Math. 30 (1978), no. 1, 33‑76.
[6] E. Babolian and J. Saeidian, Analytic approximate solutions to Burgers, Fisher, Huxley equations and two combined forms of these equations, Commun. Nonlinear Sci. Numer. Simul. 14 (2009), 1984‑1992.
[7] Y. Bai, T. Chaolu, and S. Bilige, Solving Huxley equation using an improved PINN method, Nonlinear Dyn. 105 (2021), 3439‑3450.
[8] B. Batiha, M.S.M. Noorani, and I. Hashim, Numerical simulation of the generalized Huxley equation by He's variational iteration method, Appl. Math. Comput. 186 (2007), no. 2, 1322‑1325.
[9] J.V. Beck and D.C. Murio, Combined function specification‑regularization procedure for solution of inverse heat condition problem, AIAA J. 24 (1986), 180‑185.
[10] J.M.G. Cabez, J.A.M. Garcia, and A.C. Rodriguez, A sequential algorithm of inverse heat conduction problems using singular value decomposition, Int. J. Therm. Sci. 44 (2005), 235‑244.
[11] H. Dong, Y. Xu, D. Cao, W. Zhang, Z. Yang, and X. Li, An improved teaching‑learning‑based optimization algorithm with a modified learner phase and a new mutation‑restarting phase, Knowl.‑Based Syst. 258 (2022), 109989.
[12] L. Duan and Q. Lu, Bursting oscillations near codimension‑two bifurcations in the Chay Neuron model, Int. J. Nonlinear Sci. Numer. Simul. 7 (2006), no. 1, 59‑64.
[13] S. Foadian, R. Pourgholi, and S.H. Tabasi, Cubic B‑spline method for the solution of an inverse parabolic system, Appl. Anal. 97 (2017), no. 3, 438‑465.
[14] S. Foadian, R. Pourgholi, S.H. Tabasi, and J. Damirchi, The inverse solution of the coupled nonlinear reaction‑diffusion equations by the Haar wavelets, Int. J. Comput. Math. 96 (2019), no. 1, 105‑125.
[15] S. Foadian, R. Pourgholi, and A. Esfahani, Numerical solution of the linear inverse wave equation, Int. J. Nonlinear Anal. Appl. 13 (2022), no. 2, 1907‑1926.
[16] S. Foadian, R. Pourgholi, and A. Esfahani, Numerical solution of the linear inverse wave equation, Int. J. Nonlinear Anal. Appl. 13 (2022), no. 2, 1907‑1926.
[17] A.L. Hodgkin and A.F. Huxley, A Quantitative description of ion currents and its applications to conduction and excitation in nerve membranes, J. Physiol. 117 (1952), 500‑544.
[18] M. Javidi and A. Golbabai, A new domain decomposition algorithm for generalized Burger's‑Huxley equation based on Chebyshev polynomials and preconditioning, Chaos Solitons Fractals 39 (2009), no. 2, 849‑857.
[19] Z. Jiang, F. Zou, D. Chen, S. Cao, H. Liu, and W. Guo, An ensemble multi‑swarm teaching‑learning‑based optimization algorithm for function optimization and image segmentation, Appl. Soft Comput. 130 (2022), 109653.
[20] S. Liu, T. Fan, and Q. Lu, The spike order of the winnerless competition (WLC) model and its application to the inhibition neural system, Int. J. Nonlinear Sci. Numer. Simul. 6 (2005), no. 2, 133‑138.
[21] L.B. Liu, Y. Liang, J. Zhang, and X. Bao, A robust adaptive grid method for singularly perturbed Burger‑Huxley equations, Electron. Res. Arch. 28 (2020), no. 4, 1439‑1457.
[22] R. Mohammadi, B‑spline collocation algorithm for numerical solution of the generalized Burger's‑Huxley equation, Numer. Methods Partial Differ. Equ. 29 (2013), no. 4, 1173‑1191.
[23] R.K. Mohanty, W. Dai, and D. Liu, Operator compact method of accuracy two in time and four in space for the solution of time dependent Burgers‑Huxley equation, Numer. Algorithms 70 (2015), no. 3, 591‑605.
[24] R. Pourgholi, S.H. Tabasi, and H. Zeidabadi, Numerical techniques for solving system of nonlinear inverse problem, Eng. Comput. 34 (2018), 487‑502.
[25] R.V. Rao, V.J. Savsani, and D.P. Vakharia, Teaching‑learning‑based optimization: a novel method for constrained mechanical design optimization problems, Comput.‑Aided Des. 43 (2011), 303‑315.
[26] R.V. Rao, V.J. Savsani, and D.P. Vakharia, Teaching learning‑based optimization: an optimization method for continuous non‑linear large scale problems, Inf. Sci. 183 (2012), 1‑15.
[27] R.V. Rao and V. Patel, An improved teaching‑learning‑based optimization algorithm for solving unconstrained optimization problems, Sci. Iran. 20 (2013), no. 3, 710‑720.
[28] A. Saeedi, S. Foadian, and R. Pourgholi, Applications of two numerical methods for solving inverse Benjamin‑Bona‑Mahony‑Burgers equation, Eng. Comput. 36 (2020), no. 4, 1453‑1466.
[29] C.W. Sahabandu, D. Karunarathna, P. Sewvandi, et al., A method of directly defining the inverse mapping for a nonlinear partial differential equation and for systems of nonlinear partial differential equations, Comput. Appl. Math. 40 (2021), 234.
[30] J. Satsuma, Exact Solutions of Burgers' Equation with Reaction Terms, in Topics in Soliton Theory and Exact Solvable Nonlinear Equations, 1987.
[31] G.D. Smith, Numerical Solution of Partial Differential Equations, Oxford University Press, New York, 1965.
[32] X.Y. Wang, Z.S. Zhu, and Y.K. Lu, Solitary wave solutions of the generalised Burgers‑Huxley equation, J. Phys. A: Math. Gen. 23 (1990), no. 3, 271‑274.
[33] A.M. Wazwaz, Travelling wave solutions of generalized forms of Burgers, Burgers‑KdV and Burgers‑Huxley equations, Appl. Math. Comput. 169 (2005), no. 1, 639‑656.
[34] G.J. Zhang, J.X. Xu, H. Yao, and R.X. Wei, Mechanism of bifurcation‑dependent coherence resonance of an excitable neuron model, Int. J. Nonlinear Sci. Numer. Simul. 7 (2006), no. 4, 447‑450.