Signals, Volume 3, Issue 4
2022 December - 15 articles
Cover Story: The proposed sampling methodology generates an approximation of the objective function by first taking some samples from it and then training a neural network to approximate the function. Once the neural network training process is completed, a bunch of points can be sampled from the neural network, and those with the lowest functional value will be used as starting points for the Multistart method. This way, the actual function will not be sampled, but the neural network approximating it will, which should significantly reduce the required number of function calls. Furthermore, using points with a low function value as starting points is expected to speed up the location of the global minimum. In addition, the RBF neural network is incorporated since it has a speedy training technique. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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