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New extension methods and modified preprocessing techniques can improve the prediction performance of these hybrid models in forecast experiments.
Filled triangles are used as data points in forecast experiments, whereas open triangles are not used because there are not a corresponding event in other sequences.
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The smaller events denoted by open triangles were not used as data points in our forecast experiments.
However, as aftershocks are also targeted in the forecast experiment by CSEP for Japan, the results listed in Tables 1 to 9 are for target earthquakes including aftershocks, which makes results worse when many aftershocks occur.
Even though several other papers have explicitly stated which experiment they are performing, a comparison between results in the hindcast and forecast experiments is still missing.
Recently, several ensemble forecast experiments in which heavy rainfall or local heavy rainfall was reproduced have been performed with a local ensemble transform Kalman filter (LETKF; Hunt et al. 2007; Miyoshi and Aranami 2006).
The results of this study indicate that the six hybrid models perform better in the hindcast experiment compared with the original ANN and ARMA models, while the hybrid models in the forecast experiment perform worse than the original models and the performances of WA-based and EMD-based models vary largely across different extension methods.
This paper performed earthquake forecast experiments by using numerical simulations.
In other words, the present study does not invalidate most of the results of the first RELM/CSEP forecast experiments, which focus on long-term time-invariant models.
One of the primary steps in launching an earthquake forecast experiment is to obtain a consensus among potential participants (Nanjo et al., 2011).
In a real-time forecast experiment, the history inside the forecast time window T i is unknown; therefore, for such history-dependent models, such as ETAS, Hyp2 is inadequate.
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