Abstract
In this paper, a modular neural network (MNN) architecture based on competitive clustering and a winner-takes-all strategy is proposed. In this case, the modules are obtained from clustering the training data with a competitive layer. And each module consists of a single hidden layer nonlinear autoregressive neural network. This MNN architecture can be used for short-term and long-term time series forecasting.
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