Sentence examples for moving average approach from inspiring English sources

In this paper, we propose and discuss several distributed query scheduling policies that directly consider the available cache contents by employing distributed multidimensional indexing structures and an exponential moving average approach to predicting cache contents.

The proposed prediction framework enables the prediction of future values of the network response time, employing load-prediction techniques based on the exponential moving average approach presented in [4, 5].

For the calculation of normalized ΔF/F0 data with the moving average approach, a sliding window of 0.8 s was used to calculate F0.

For assessment of gene expression changes at the 1q12/2p breakpoint sequence in CH1 cells, a moving average approach with 500 kb windows was used to compare gene expression values to similar sized regions of equal copy number in the rest of the genome (4833 probes).

Regardless of the approach to categorize FPG, there was a sharp increase in retinopathy prevalence after 5.8 mmol/l (95% CI 5.1 6.1 for the decile approach, 5.2 6.8 for the Pima Indian approach, and 5.3 6.3 by the moving average approach) (all P values <0.05).

Regardless of the approach used, there was a sharp increase in retinopathy prevalence above an A1C of 5.5%95%5% CI 5.3 5.6 for the decile approach, 5.1 6.1 for the Pima Indian approach, and 5.3 5.8 by the moving average approach) (all P values <0.05).

A Bayesian autoregressive moving average (ARMA) approach is chosen to model the time series input due to its capability to represent both natural variability and epistemic uncertainty due to limited data.

Uncertainties associated with wholesale electricity market price, clients' consumption and power output of wind resources are considered through auto regressive integrated moving average (ARIMA) approach.

Fisher and Black (2006) proposed an autoregressive moving average (ARMA) approach [61], and Shpigelman et al. (2008) demonstrated the kernel autoregressive moving average (KARMA) method with the spikernel in closed-loop BMI [62].

Enriched regions with a false discovery rate (FDR) of 1.0% (0.01) were determined by comparing triplicate samples of AhRTCDD to triplicate IgGTCDD using a moving average (MA) approach with default settings in TileMap v2 [ 85].

To verify the robustness of our findings at the suggestion of one of the reviewers, we subsequently repeated analyses using the Box Jenkins autoregressive integrated moving average (ARIMA) approach.