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Table 2 shows approximated solutions, absolute errors, and exact solution in some points.
We can thus only find approximated solutions by using the most likely state sequence.
In most cases, the solution of a FDE does not exist in terms of a finite number of elementary functions; it is therefore fundamental to device numerical methods in order to practically evaluate approximated solutions by means of difference schemes or other alternative approaches (e.g., see [14 19]).
Absolute errors L ∞, root mean square error (RMS), and L 2 are computed according to the following formulas: L ∞ − Error = max 1 ≤ i ≤ n | e i |, RMS − Error = ( ∑ i = 1 n e i 2 n ) 1 / 2, and L 2 − Error = ( ∑ i = 1 n e i 2 ) 1 / 2, where e i = ( u i − U i ), u i are approximated solutions and U i are exact solutions.
Approximated solutions for both the crack propagation path and the stress intensity factor are derived, and the fatigue predictions using this simple analytical method are finally compared with the numerical results.
Since, this problem is NP-hard, we devise approximation algorithms that provide guarantees on the quality of the approximated solutions against the optimal solutions.
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Table 8 shows approximated solution, noisy solutions, and exact solution.
It tells us to go for approximation — more approximate solutions, which find many right answers, but not all right answers.
Einstein made his own early predictions of observable phenomena by using partial and approximate solutions.
approximate solutions.
Approximate solutions of Eqs.
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