This book focuses on the fields of hybrid intelligent systems based
on fuzzy systems, neural networks, bio-inspired algorithms and time
series. This book describes the construction of ensembles of
Interval Type-2 Fuzzy Neural Networks models and the optimization
of their fuzzy integrators with bio-inspired algorithms for time
series prediction. Interval type-2 and type-1 fuzzy systems are
used to integrate the outputs of the Ensemble of Interval Type-2
Fuzzy Neural Network models. Genetic Algorithms and Particle Swarm
Optimization are the Bio-Inspired algorithms used for the
optimization of the fuzzy response integrators. The Mackey-Glass,
Mexican Stock Exchange, Dow Jones and NASDAQ time series are used
to test of performance of the proposed method. Prediction errors
are evaluated by the following metrics: Mean Absolute Error, Mean
Square Error, Root Mean Square Error, Mean Percentage Error and
Mean Absolute Percentage Error. The proposed prediction model
outperforms state of the art methods in predicting the particular
time series considered in this work.
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