Abstract
Grey neural network is an innovative intelligent computing approach combing grey system model and neural network, which makes full use of the similarities and complementarity between grey system model and neural network to settle the disadvantage of applying Grey model and Neural Network separately. Some optimization algorithms such as genetic algorithm are also employed to modeling and optimizaion of grey neural network. Many typical grey neural work models such as GNNM(1,1),GRBF,DGRBF, GA-GRBF and so on are proposed and applied in this paper. A lot of comparative experimental results show that grey neural network models are capable of predicting a small sample of data accurately, easily and conveniently. The key technologies, research hotspots, difficulties and further development of grey neural network are discussed in this paper.
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Yuan, J., Zhong, L., Li, X., Li, J. (2008). Modeling of Grey Neural Network and Its Applications. In: Kang, L., Cai, Z., Yan, X., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2008. Lecture Notes in Computer Science, vol 5370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92137-0_33
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DOI: https://doi.org/10.1007/978-3-540-92137-0_33
Publisher Name: Springer, Berlin, Heidelberg
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