A fuzzy neural network with fuzzy impact grades
Neurocomputing
Multivariate Student-t self-organizing maps
Neural Networks
Neural networks cartridges for data mining on time series
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A probabilistic fuzzy approach to modeling nonlinear systems
Neurocomputing
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Modular state space of echo state network
Neurocomputing
Hi-index | 0.00 |
This paper presents an investigation into the use of the time delay coordinate embedding technique in the multi-input-multi-output-adaptive-network-based fuzzy inference system (MANFIS) for chaotic time series prediction. The inputs of the MANFIS are embedded-phase-space (EPS) vectors preprocessed from the time series under test while the output time series is extracted from the EPS vectors. With such EPS preprocessing, the prediction accuracy of the MANFIS is found to be significantly improved. The proposed system will be tested with a periodic and the Mackey-Glass chaotic time series by comparing the prediction accuracy with and without EPS preprocessing. A moving root-mean-square error is used to monitor the error along the prediction horizon and to tune the membership functions in the MANFIS.