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Fig. 4 Representation of the solution.
Fig. 6 Simple representation of the solution.
Figure 4 displays the representation of the solution.
The explicit representation of the solution is also given.
The integral representation of the solution u to problem (P1) can be written as (3.1).
The main difference between genetic programming and genetic algorithm is the representation of the solution.
Fig. 9 Representation of the solution space with respect to the quasistatic equilibrium line.
First, an appropriate finite or discrete representation of the solution must be chosen.
Furthermore, an implicit representation of the solution (v, f) is obtained.
(3) inverse transformation and derivation of the exact representation of the solution in the original variables.
Vanishing moments of the basis functions permit a sparse representation of the solution and operators.
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