Gene expression programming (GEP) is a mathematical model that can be used to optimize complex systems. It has not only limited to specific problems, but also has good robustness in solving various problems, which has been applied in many disciplines such as biochemistry, physics, and mathematics. In this paper, the IGEP algorithm was proposed based on the optimization of GEP algorithm, and the algorithm for solving the inverse problem of parameter identification of partial differential equations based on this algorithm was studied. The structure and steps of GEP algorithm were analyzed firstly, and the GEP (IGEP) based on improved mutation operator was proposed. The algorithm advantage of IGEP for solving the inverse problem of partial differential equations was discussed. In addition, the simulation experiments were carried out to prove the feasibility and superiority of the proposed algorithm.
IGEP Partial differential equation Parameter identification inverse problem Solving algorithm Research
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The study was supported by “Science and Technology Project of China Railway Corporation, China (Grant No. 1341324011)” and “National key innovation prediction project of Mudanjiang Normal University (Grant No. GY201205)”.
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