Sentence examples for prediction period from inspiring English sources

25 To assess the hypothesis of a loss in discrimination ability due to a longer prediction period, we estimated the 10-year predicted probability of events in our database, using the same set of risk factors but with shorter follow-up period, that is, up to the end of 2002 for all the participants (number of events 234 in men, 79 in women).

(3) Predicted Mean: Represents the mean of the predictions in the prediction period.

To evaluate the predictions from a computer program, the program is provided with electric load data, and additional data such as outdoor air temperature, from a "training period" of at least several months duration, and used to predict the energy use as a function of time during the subsequent "prediction period".

To address these questions, we assessed the relative importance of the current hydrological state and weather during the prediction period.

The relative importance of the initial hydrological state and weather during the prediction period was evaluated by comparing the simulations of both experiments to a common reference simulation.

There were 37 eggs reporting on September 11, and over the 4 hours and 10 minutes of the prediction period, their accumlated Chisquare was 15332 on 15000 degrees of freedom.

Moosavi et al. (2013) applied hybrid models based on Wavelet, Wavelet-ANFIS and Wavelet-ANN for groundwater level forecasting during different prediction periods.

In the first group the goal was to evaluate the best techniques, time period and set of variables while the second group of experiments was designed to evaluate longer prediction periods based on the best set of variables and techniques.

However, this model requires measurements of CPB temperature during the prediction periods and does not consider the effects of the mixture recipe and mechanical load (e.g., stress) and deformation (e.g., consolidation); that is, the model is empirical.

In order to verify the quality of the proposed approach to identify trends over longer periods, additional experiments have been conducted fixing the dataset training period between years 1991 and 2005 and varying the prediction periods between the years 2006 and 2011 for testing.

The comparison between the algorithmic predictions and the clinician predictions are summarised in table 2. The model had comparable performance to that of the clinicians, with the performance of the machine-learning model marginally better (AUC ranging from 0.76 to 0.87) than that of the clinicians (AUC ranging from 0.75 to 0.79) for all three prediction periods.