An improved imperialist competitive algorithm for solving an inverse form of the Huxley equation

Iranian Journal of Numerical Analysis and Optimization

مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 12 اردیبهشت 1403

نوع مقاله: Research Article

شناسه دیجیتال (DOI): 10.22067/ijnao.2024.86692.1384

نویسندگان

Hassan Dana Mazraeh¹؛ Kourosh Parand^{* 1، 2}؛ Hadi Farahani¹؛ Saeed Reza Kheradpisheh¹

¹Department of Computer and Data Sciences, Faculty of Mathematical Sciences, Shahid Beheshti University, G.C. Tehran, Iran.

²Department of Cognitive Modeling, Institute for Cognitive and Brain Sciences, Shahid Beheshti University, G.C. Tehran, Iran.

چکیده

In this paper, we present an improved imperialist competitive algorithm for solving an inverse form of the Huxley equation, which is a nonlinear partial differential equation. To show the effectiveness of our proposed algorithm, we conducted a comparative analysis with the original imperialist competitive algorithm and a genetic algorithm. The improvement suggested in this study made the original imperialist competitive algorithm a more powerful method for function approximation. The numerical results show that the improved imperialist competitive algorithm is an efficient algorithm for determining the unknown boundary conditions of the Huxley equation and solving the inverse form of nonlinear partial differential equations.

کلیدواژه‌ها

Huxley equation؛ Imperialist competitive algorithm؛ Partial differential equations؛ Meta-heuristic algorithms؛ Genetic algorithm