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Comparing with those methods, our convergent strategy does not rely on golden standard genes, while it examines many genes simultaneously.
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Figure 1 is the 3D representation of the exact solution and regularized solutions when ϵ = 10 − 1, ϵ = 10 − 2 and ϵ = 10 − 3. Figure 2 shows graphs of section cut of these solutions at value y = 0.5 when ϵ = 10 − 1, ϵ = 10 − 2 and ϵ = 10 − 3. It is easy to see that our methods are stably convergent.
1) Compared to the GA method, HLO method, BHS method and DBPSO method, ASHLO method has good convergent property and robustness.
Algorithm that combines the rapid local convergence of Newton Raphson method with globally convergent method for non-linear systems of equations is applied for theoretically obtained differential spectra.
Moreover, we show that the proposed methods are convergent with temporal order one in probability.
The last two of these three methods are convergent, moreover all the three methods work for both short term and long term options.
The methods are convergent as long as the underlying solution remains fairly regular (and a sign condition holds in the case without surface tension).
The results show that the methods are convergent with a good accuracy.
A mixed methods triangulated convergent design.
We employed both qualitative and quantitative data collection methods in convergent design.
Letting (alpha=0.3) and (p=1.52), the numerical results at (t=1) in time with (M=300) are displayed in Table 2, while the corresponding results in space with (N=5mbox000) are tabulated in Table 3, where our method yields the convergent approximationswith the desirable accuracy.
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