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Co-evolving data driven models and test data sets with the application to forecast chaotic time series.

, and . IEEE Congress on Evolutionary Computation, page 14-20. IEEE, (2011)

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Spacecraft attitude estimation with the aid of Locally Linear Neurofuzzy models and multi sensor data fusion approaches., , and . ICARA, page 127-132. IEEE, (2009)Introducing adaptive neurofuzzy modeling with online learning method for prediction of time-varying solar and geomagnetic activity indices., , , and . Expert Syst. Appl., 37 (12): 8267-8277 (2010)Input Variables Selection Using Mutual Information for Neuro Fuzzy Modeling with the Application to Time Series Forecasting., , and . IJCNN, page 1121-1126. IEEE, (2007)Extracting the main patterns of natural time series for long-term neurofuzzy prediction., , , , and . Neural Comput. Appl., 16 (4-5): 383-393 (2007)Evolved digital ecosystems: Dynamic steady state, not optimal fixed point., , , , , , and . ECAL, page 126-133. MIT Press, (2013)Fuzzy descriptor systems and spectral analysis for chaotic time series prediction., , , , and . Neural Comput. Appl., 18 (8): 991-1004 (2009)A Rough Set Approach Aim to Space Weather and Solar Storms Prediction., , , and . ICCSA (1), volume 6782 of Lecture Notes in Computer Science, page 588-601. Springer, (2011)Evolution of Autonomous Hierarchy Formation and Maintenance., and . ALIFE, page 366-367. MIT Press, (2014)Forecasting Solar Activity Using Co-evolution of Models and Tests., , , and . ISDA, page 629-634. IEEE Computer Society, (2007)Modulation identification using combined classifiers and co-evolution of classifiers and tests., , and . FUSION, page 1-8. IEEE, (2007)