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It is very significant for us to predict future energy consumption accurately. As for China's energy consumption annual time series, the sample size is relatively small. This study combines the traditional auto-regressive model with group method of data handling (GMDH) suitable for small sample prediction, and proposes a novel GMDH based auto-regressive (GAR) model. This model can finish the modeling...
For financial investment, the problem that we often encounter is how to extract information hidden in the volatile and noise data and forecast it into future. This study proposes a novel three-stage neural-network-based nonlinear weighted ensemble model. In proposed model, three different types neural-network base models, i.e., Elman network, generalized regression neural network (GRNN) and wavelet...
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