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"Further, we demonstrated the robustness of our algorithm by solving examples not describable by our grammar.
Solving examples and understanding the solution is of course one of the most popular activities in mathematical learning.
For the adaptive division and bisection the computational time of solving examples with larger N ranging from 600 to 1500 are listed in Table 2.
From Table 1, it can be seen easily that the proposed algorithm requires less computational time for solving Examples 1-5 compared with the ones in [19, 21] with the same (varepsilon>0) value.
Although learning by solving examples is adopted in general education, it may not be sufficiently effective in fostering learner problem posing because cognitive skills differ between problem solving and problem posing.
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Figure 1 Numerical results for solving Example 1 with Algorithm 1 Figure 2 Numerical results for solving Example 1 with smoothing gradient method.
Using the proposed Algorithm 1, we obtain the results for solving Example 6.1 and Example 6.2.
Let (varepsilon=0.01 ), use the proposed Algorithm 2, we obtain the results for solving Example 6.3, Example 6.4, and Example 6.5.
There are several educational activities that are supported by these systems such as: problem solving, example review, educational games, etc.
The numerical results are given in Figs. 3 and 4. Figure 3 Numerical results for solving Example 2 with Algorithm 1 Figure 4 Numerical results for solving Example 2 with smoothing gradient method.
The trend of objective function improvements using the SA algorithm for solving Example 1 is illustrated in Fig. 2.
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