It is obvious that the accuracy of Algorithm 2 is good.
The simulations in Figure 8(c) also evaluate the accuracy of Algorithm Coverage Computation.
Through simple comparison, Antweiler and Frank (2004) found that the accuracy of algorithm classification is actually higher than that of manual classification.
Experimental results showed that the accuracy of algorithm was as high as 99%, and the processing speed could satisfy the real-time requirement in engineering.
In the case of neither Mathematica nor Matlab finding a solution (nC for not converging), the accuracy of Algorithm 3.3's output (x_{0}) is tested through the parameter μ.
For every case in each configuration, we compare the accuracy of Algorithm 3 with the BIHT, RFPI, LP, and GAMP by computing the average of values of the four metrics over 100 trials.
In this section, we illustrate the accuracy of Algorithm 1. From the Taylor expansion at ((x_{j},t_{n+1})), we have the following truncation errors for the Crank Nicolson scheme (4) and Saul 'yevasymmetric schemes (5)–(8), respectively.
The accuracy of algorithm is verified by comparing the numerical results of static, free vibration and simplified moving force problems analysis with the available exact solutions and other numerical results in the literature.
