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.
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Acknowledgements
This work is supported by the National Natural Science Foundation of China with the Grant No. 61573157, the Fund of Natural Science Foundation of Guangdong Province of China with the Grant No. 2014A030313454, Guangdong Province Science and Technology Research Project with the Grant No. yue ke gui hua zi 2013-137.
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Li, K., Chen, Y., He, J. (2016). The Research of Solving Inverse Problems of Complex Differential Equations. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 682. Springer, Singapore. https://doi.org/10.1007/978-981-10-3614-9_64
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DOI: https://doi.org/10.1007/978-981-10-3614-9_64
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