| 摘要 |
Described is a system for temporal prediction. The system includes an extraction module, a mapping module, and a prediction module. The extraction module is configured to receive X(1), . . . X(n) historical samples of a time series and utilize a genetic algorithm to extract deterministic features in the time series. The mapping module is configured to receive the deterministic features and utilize a learning algorithm to map the deterministic features to a predicted x(n+1) sample of the time series. Finally, the prediction module is configured to utilize a cascaded computing structure having k levels of prediction to generate a predicted x(n+k) sample. The predicted x(n+k) sample is a final temporal prediction for k future samples.
|
