Abstract
A novel approach of function mining algorithm based on co-evolutionary gene expression programming (GEP-DE) which combines gene expression programming (GEP) and differential evolution (DE) was proposed in this paper. GEP-DE divides the function mining process of each generation into 2 phases: in the first phase, GEP focuses on determining the structure of function expression with fixed constant set, and in the second one, DE focuses on optimizing the constant parameters of the function which obtained in the first phase. The control experiments validate the superiority of GEP-DE, and GEP-DE performs excellently in the wheat aphid population forecast problem.
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Wang, C., Ma, C., Zhang, X., Zhang, K., Zhu, W. (2014). Co-evolutionary Gene Expression Programming and Its Application in Wheat Aphid Population Forecast Modelling. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8794. Springer, Cham. https://doi.org/10.1007/978-3-319-11857-4_31
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DOI: https://doi.org/10.1007/978-3-319-11857-4_31
Publisher Name: Springer, Cham
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