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Time Series Prediction Using Ensembles of ANFIS Models with Particle Swarm Optimization of the Fuzzy Integrators.

, , and . MICAI (1), volume 9413 of Lecture Notes in Computer Science, page 472-483. Springer, (2015)

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A new approach for time series prediction using ensembles of ANFIS models., , , and . Expert Syst. Appl., 39 (3): 3494-3506 (2012)A New Approach for Time Series Prediction Using Ensembles of IT2FNN Models with Optimization of Fuzzy Integrators., , and . Int. J. Fuzzy Syst., 20 (3): 701-728 (2018)A new approach for time series prediction using ensembles of ANFIS models with interval type-2 and type-1 fuzzy integrators., , and . CIFEr, page 68-73. IEEE, (2013)Particle Swarm Optimization of the Fuzzy Integrators for Time Series Prediction Using Ensemble of IT2FNN Architectures., , and . Nature-Inspired Design of Hybrid Intelligent Systems, volume 667 of Studies in Computational Intelligence, Springer, (2017)Time Series Prediction Using Ensembles of ANFIS Models with Particle Swarm Optimization of the Fuzzy Integrators., , and . MICAI (1), volume 9413 of Lecture Notes in Computer Science, page 472-483. Springer, (2015)Time series prediction using ensembles of ANFIS models with genetic optimization of interval type-2 and type-1 fuzzy integrators., , and . Int. J. Hybrid Intell. Syst., 11 (3): 211-226 (2014)Optimization of the Fuzzy Integrators in Ensembles of ANFIS Model for Time Series Prediction: The case of Mackey-Glass., and . IFSA-EUSFLAT, Atlantis Press, (2015)A New Approach to Multiple Time Series Prediction Using MIMO Fuzzy Aggregation Models with Modular Neural Networks., , , and . Int. J. Fuzzy Syst., 21 (5): 1629-1648 (2019)Genetic Optimization of Type-1 and Interval Type-2 Fuzzy Integrators in Ensembles of ANFIS Models for Time Series Prediction., , and . WCSC, volume 342 of Studies in Fuzziness and Soft Computing, page 331-351. Springer, (2014)Optimization of the Interval Type-2 Fuzzy Integrators in Ensembles of ANFIS Models for Time Series Prediction: Case of the Mexican Stock Exchange., and . Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization, volume 601 of Studies in Computational Intelligence, Springer, (2015)