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Ensembles of Type 2 Fuzzy Neural Mod...
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Castillo, Oscar.
Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction/ by Jesus Soto, Patricia Melin, Oscar Castillo.
作者:
Soto, Jesus.
其他作者:
Melin, Patricia.
面頁冊數:
VIII, 97 p. 101 illus., 73 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Computational intelligence. -
電子資源:
https://doi.org/10.1007/978-3-319-71264-2
ISBN:
9783319712642
Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction
Soto, Jesus.
Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction
[electronic resource] /by Jesus Soto, Patricia Melin, Oscar Castillo. - 1st ed. 2018. - VIII, 97 p. 101 illus., 73 illus. in color.online resource. - SpringerBriefs in Computational Intelligence,2625-3704. - SpringerBriefs in Computational Intelligence,.
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. .
ISBN: 9783319712642
Standard No.: 10.1007/978-3-319-71264-2doiSubjects--Topical Terms:
568984
Computational intelligence.
LC Class. No.: Q342
Dewey Class. No.: 006.3
Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction
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