@inbook{d3ed7715244248138c4556c24896e1c4,
title = "The Research of Solving Inverse Problems of Complex Differential Equations",
abstract = "There are various complicated or non-linear system varying with the time (dynamic system) in the reality and scientific aspects, and such dynamic system is usually expressed by the differential equations. In this paper, a new GEP-based algorithm is put forward to solve the inverse problems of ordinary differential equation (ODE) and complex high-order differential equations by taking advantage of the self-adaptability, self-organization and self-study of Gene Expression Programming (GEP), which is difficult to solve by use traditional methods. Experiments show that this improved GEP algorithm can be used to solve the optimization problems of ordinary differential equations and complex differential equations in shorter time and with higher precision comparing with the traditional ones",
keywords = "gene expression programming, system of ordinary differential equations, inverse problem, Runge-Kutta algorithm",
author = "Kangshun Li and Yan Chen and Jun He",
year = "2017",
month = jan,
day = "8",
doi = "10.1007/978-981-10-3614-9_64",
language = "English",
isbn = "978-981-10-3613-2",
series = "Communications in Computer and Information Science",
publisher = "Springer Nature",
pages = "518--523",
editor = "Maoguo Gong and Linqiang Pen and Tao Song and Gexiang Zhang",
booktitle = "Bio-inspired Computing - Theories and Applications",
address = "Switzerland",
edition = "Part 11",
note = "11th International Conference, BIC-TA 2016 ; Conference date: 28-10-2016 Through 30-10-2016",
}