Adaptive neuro-fuzzy inference system

ANFIS—adaptive neuro-fuzzy inference system... [Pg.462]

In Example 8.9, the performance of this adaptive neuro-fuzzy inference system is demonstrated for classification of two-dimensional data. [Pg.331]

Example 8.10 Adaptive neuro-fuzzy inference system (ANFIS)... [Pg.331]

Cai CH, Ehi D, Liu ZY (2003) Battery state-of-charge (SOC) estimation using adaptive neuro-fuzzy inference system (ANFIS). In Proceedings of the 12th IEEE international conference on fuzzy systems, FUZZ 03, pp 1068-1073. IEEE... [Pg.46]

Justesen KK, Andreasen SJ, Shaker HR et al (2013) Gas composition modeling in a reformed methanol fuel cell system using adaptive neuro-fuzzy inference systems. Int J Hydrog Energy 38 10577-10584... [Pg.486]

Neuro fuzzy modeling is a useful technique that combines the advantages of neural networks and fuzzy inference systems. In this approach, the fuzzy model is architecturally the same as a neural network. In this case one could use, for example error back-propagation to train the network to find the parameters of the fuzzy model. The most well-known method is the so-called ANFIS method the Adaptive-Network based Fuzzy Inference System. The method will be explained in this chapter and several examples will be developed as an illustration. [Pg.399]

Big Chemical Encyclopedia