Abstract
Conjugate gradient methods can be used with advantages such as fast convergence and low memory requirement in real applications. A conjugate gradient-based neuro-fuzzy learning algorithm for zero-order Takagi-Sugeno inference systems is proposed in this paper. Compared with the existing gradient-based algorithm, this method enhances the learning performance.
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Gao, T., Li, L., Zhang, Z., Sun, Z., & Wang, J. (2018). A new parameter identification method for type-1 TS fuzzy neural network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10878 LNCS, pp. 200–207). Springer Verlag. https://doi.org/10.1007/978-3-319-92537-0_24
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