Paper Info
Title
Optimization of Ensemble Neural Networks with Type-1 and Type-2 Fuzzy Integration for Prediction of the Taiwan Stock Exchange
Abstract
This paper describes an optimization method based on genetic algorithms and particle swarm optimization for ensemble neural networks with type-1 and type-2 fuzzy aggregation for forecasting complex time series. The time series that was considered in this paper to compare the hybrid approach with traditional methods is the Taiwan Stock Exchange (TAIEX), and the results shown are for the optimization of the structure of the ensemble neural network with type-1 and type-2 fuzzy integration. Simulation results show that the ensemble approach produces good prediction of the Taiwan Stock Exchange.
Year
DOI
Venue
2016
10.1007/978-3-319-75408-6_13
Studies in Fuzziness and Soft Computing
Keywords
DocType
Volume
Ensemble neural networks,Optimization,Genetic algorithms,Time series prediction,Particle swarm
Conference
361
ISSN
Citations 
PageRank 
1434-9922
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Martha Pulido191.07
Patricia Melin24009259.43