The phrase "ahead steps" is not correct in standard written English.
It may be intended to convey a sense of future actions or plans, but it lacks clarity and proper grammatical structure.
Example: "We need to outline the ahead steps for the project to ensure we stay on track."
Alternatives: "next steps" or "future actions".
The Senator moved ahead step by step to build a consensus for the bill.
In order to assess the performance of the proposed model when forecasting for a range of look-ahead steps, simulation studies of (1sim 20) look-ahead steps are conducted and the forecasting performance is evaluated using NMAE and NRMSE.
Furthermore, NMAE and NRMSE are improved by 69.32 and 69.02 at 6 look-ahead steps, which is the biggest improvement, and by 14.62 and 17.06 at 20 look-ahead steps, which is the least, compared to the Per.
Take the case of forecasting 4 look-ahead steps using the December data of the Elia data set for example.
Fig. 7 Joint recovery and prediction for 10 (top) and 20 (bottom) look-ahead steps on SensorScope data.
Fig. 8 Joint recovery and prediction for 10 (top) and 20 (bottom) look-ahead steps on Intel-Berkeley data.
The forecast results for 4, 12, and 20 look-ahead steps have been demonstrated in Table 7, and the SSA-LSH-SVR is superior to SSA-K-means-SVR in all cases.
For the purpose of making a more comprehensive study, numerical results for 4, 12, and 20 look-ahead steps have been summarised in Tables 3, 4 5 and 6.
To examine the performance of the proposed model on various data sets, the NMAEs and NRMSEs of the proposed model on the four data sets for (1sim 20) look-ahead steps are plotted in Figs. 9 and 10.
The forecast results of 4 look-ahead steps in March based on the proposed model are shown in Fig. 5, which shows the forecast curve almost coincides with the actual one.
A series of experiments are conducted on the Elia data set whose sample interval is 15 minutes, and the results show that as the number of look-ahead steps increases, a more accurate forecast could be obtained by increasing the embedding dimension L; yet, when L reaches a critical point, the accuracy begins to decrease.
