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    Fuzzy descriptor systems and spectral analysis for chaotic time series prediction

    , Article Neural Computing and Applications ; Volume 18, Issue 8 , 2009 , Pages 991-1004 ; 09410643 (ISSN) Mirmomeni, M ; Lucas, C ; Shafiee, M ; Nadjar Araabi, B ; Kamaliha, E ; Sharif University of Technology
    Predicting future behavior of chaotic time series and systems is a challenging area in the literature of nonlinear systems. The prediction accuracy of chaotic time series is extremely dependent on the model and the learning algorithm. In addition, the generalization property of the proposed models trained by limited observations is of great importance. In the past two decades, singular or descriptor systems and related fuzzy descriptor models have been the subjects of interest due to their many practical applications in modeling complex phenomena. In this study fuzzy descriptor models, as a more recent neurofuzzy realization of locally linear descriptor systems, which have led to the... 

    Long-term prediction of solar and geomagnetic activity daily time series using singular spectrum analysis and fuzzy descriptor models

    , Article Earth, Planets and Space ; Volume 61, Issue 9 , 2009 , Pages 1089-1101 ; 13438832 (ISSN) Mirmomeni, M ; Kamaliha, E ; Shafiee, M ; Lucas, C ; Sharif University of Technology
    Of the various conditions that affect space weather, Sun-driven phenomena are the most dominant. Cyclic solar activity has a significant effect on the Earth, its climate, satellites, and space missions. In recent years, space weather hazards have become a major area of investigation, especially due to the advent of satellite technology. As such, the design of reliable alerting and warning systems is of utmost importance, and international collaboration is needed to develop accurate short-term and long-term prediction methodologies. Several methods have been proposed and implemented for the prediction of solar and geomagnetic activity indices, but problems in predicting the exact time and...