Multiclassifier Systems: Back to the Future
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Information Sciences: an International Journal
Dynamic support vector machines for non-stationary time series forecasting
Intelligent Data Analysis
Artificial Intelligence Review
Adaptive fuzzy system to forecast financial time series volatility
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Introduces a neural network capable of dynamically adapting its architecture to realize time variant nonlinear input-output maps. This network has its roots in the mixture of experts framework but uses a localized model for the gating network. Modules or experts are grown or pruned depending on the complexity of the modeling problem. The structural adaptation procedure addresses the model selection problem and typically leads to much better parameter estimation. Batch mode learning equations are extended to obtain online update rules enabling the network to model time varying environments. Simulation results are presented throughout the paper to support the proposed techniques