Sentence examples for algorithm performance metrics from inspiring English sources

The learning algorithm performance metrics considered here is the distance d t (in dB) between the secondary SINRs obtained with the multi-agent Q-learning algorithm and the secondary SINRs given by the optimal allocation algorithm: d t = ∑ l = 1 N SINR t, l s - SINR ^ t, l s 2 t ∈ { 1, …, K } (34).

Table 13 shows the algorithms' performance metrics.

To evaluate the algorithm performance, two metrics have been used which are listed below: 1. True Positive Rate (TPR) or sensitivity which is defined as: TPR = TP TP + FN (16)  .

To evaluate the accuracy of the clone deconvolution algorithm, two performance metrics, recall and precision, were used.

To contrast the performance of different algorithms, two performance metrics are used.

As shown by Tables 6 and 7 (and Figs. 3 and 4), the machine learning algorithms produced performance metrics that generally exceeded that of the semi-quantitative methods on the same data.

From the two GSPN descriptions, using a fixed point algorithm, several interesting performance metrics referring to the TCP connections can be derived.

Because of the diversity of potential outputs from the LTS data, we evaluated algorithm performance against summary metrics for disturbance, recovery, and stability, both for capture of events and longer-duration processes.

Our third goal is to analyze the performance of the proposed 5CVN-adroit algorithm over various performance metrics, including packet delivery ratio, average response time, routing overhead ratio, and packet collision ratio.

We demonstrate using simulations, that our algorithm outperforms two state-of-the-art algorithms in key performance metrics.

The effectiveness of the proposed algorithms is demonstrated through rigorous simulations and comparisons with some of the existing algorithms over several performance metrics.