Sentence examples for prediction size from inspiring English sources

Table 1 Comparison of size of predicted data Study Prediction size (h) Ref. [20] 50 Ref. [21] 50 Ref. [16] 45 Present study 1,314.

Regarding the sufficiency of the prediction size to be used for evaluation of the proposed networks, Table 1 compares the size of the predicted data of the present study to the data size related to prediction goals of recent similar studies.

Figure 11 Reinforcement learning using WINTER algorithm with double study time in walking scenario: (a) initial prediction window size is set to 0. 04 and the future testing window size is set to 0.06; (b) initial prediction window size is set to 0.06 and the future testing window size is set to 0.04.

Figure 10 Reinforcement learning using WINTER algorithm in walking scenario: (a) initial prediction window size is set to 0. 08 and the future testing window size is set to 0.12; (b) initial prediction window size is set to 0.12 and the future testing window size is set to 0.08.

We fitted fixed factors of age (both linear and quadratic; prediction 1a), size (prediction 2a) and inbreeding (prediction 3a) and included interactions between inbreeding and (i) age and (ii) size to test whether inbreeding depressed these measures of male quality and reduced the likelihood of a male becoming territorial.

It also provides an example, which looks at the prediction of size effects for notches.

Adaptive rule of choosing a suitable (rho_{k+1}) as the start prediction step size for the next iteration.

(12)   Step 5. Adaptive rule of choosing a suitable (rho_{k+1}) as the start prediction step size for the next iteration.

In contrast, with a prediction window size of 0, the STA needs to share during 4 time slots.

Furthermore, a fuzzy grey cognitive map (FGCM -based decision tool is built to regulate the RPIGM prediction step size to maximize the control eFGCM -based

This measure, termed absolute difference, gives the same prediction interval size for all predictions for a given confidence level, but in turn does not require any error model to be fitted and can thus lessen the computational demands.