Exact(3)
Initial value for iteration.
① Initial value for iteration The initial W can be configured by the peak avoidance method mentioned above.
The initial value for iteration could be chosen as little greater than −λ M. On the contrary, an improper great initial value may lead to invalid value less than the lower bound of λ. (3) ESBW is achieved by using λ ̂ in (29). .
Similar(57)
Figure 14 depicts these values for iteration larger than 64.
Table 3 Key GA behavioral parameters values applied to four runs and the optimal objective function value found after 2000 iterations Run 1 Run 2 Run 3 Run 4 P m 0.8 0.5 0.2 Variable P c 0.2 0.5 0.8 Optimal solution found TMD (m) 2352 2352 2354 2352 The optimal objective function value for each iteration of each run is illustrated as trends in Fig. 6 (Case 1).
However, at the cost of slightly more computational time, the CCS using l2-Sl0-CG yieldslightlyly better performance than the CCS using OMP or FISTA, and the threshold value for termination iteration in the l2-Sl0 algorishm is easier to be set.
To test the performance regarding the initial value for the iteration process we have chosen two different initial approximations: firstly the zero vector x 0 = ( 0, 0, 0, 0, 0 ) T and secondly x 0 = ( 0, 0, 0, 51.5, − 4.8 ) T that represents zero pitch angle deviation and a mass imbalance of 51.8 kgm at an angle of −5∘.
The standard deviation of this value for each iteration increased with the value of K, and was very high when K > 5.
Nonetheless this research emphasizes the importance of normalization based on properly defined normals and shows the added value of iteration for proper assessment of such normals.
where OFV and OFV B are the objective function values for this iteration and are the best computed one until this iteration.
After a burn-in of 5000 updates, 100,000 iterations were performed and convergence was checked using trace plots of the sample values for each iteration.
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