Results of a simulation test with a two-dimensional nonlinear function show that improved network has high convergence rate and good generalization capability.

The improved T–S fuzzy neural network (ITSFNN) has a compact structure, high training speed, good simulation precision, and generalization ability.

The improved algorithm introduces adaptive learning rateη and momentum factor γ into the learning algorithm which help stabilize the network and makes ...

An improved training algorithm in fuzzy neural network is proposed which takes vantage of the excellent learning and expression ability of fuzzy neural ...

In view of all these above, this paper proposes an improved training algorithm in fuzzy neural network which takes vantage of the excellent learning and ...

An improved TS fuzzy neural network is proposed in this paper, which promotes the accuracies of system recognition for TS fuzzy neural network.

This proposed model has fewer parameters thanstandard BP network under the same conditions, and outperforms Mamdani fuzzy system based HHFNN and standard BP ...

This paper reviews the application of fuzzy theory and its combination with artificial neural-network technology for remote sensing information extraction.

In view of all these above, this paper proposes an improved training algorithm in fuzzy neural network which takes vantage of the excellent learning and ...

An improved T-S fuzzy neural network based on declination compensation is proposed in this paper, which increases the accuracy of system identification by ...