Ensemble neural network with type-1 and type-2 fuzzy integration for time series prediction and its optimization with PSO

Abstract

This paper describes the design of ensemble neural networks using Particle Swarm Optimization (PSO) for time series prediction with Type-1 and Type-2 Fuzzy Integration. The time series that is being considered in this work is the Mackey-Glass benchmark time series. Simulation results show that the ensemble approach produces good prediction of the Mackey-Glass time series.