In most literature dealing with evolutionary algorithms the stopping criterion consists of reaching a certain number of objective function evaluations (or a number of generations, respectively). A disadvantage is that the number of function evaluations that is necessary for convergence is unknown a priori, so trialand-error methods have to be applied for finding a suitable number. By using othe...

Several traditional stopping criteria in Genetic Algorithms (GAs) are applied to the optimization process of a typical laminated composite plate. The results show that neither of the criteria of the type of statistical parameters, nor those of the kinds of theoretical models performs satisfactorily in determining the interruption point for the GA process. Here, considering the configuration of ...

We propose a solution on the stopping criterion in segmenting inhomogeneous DNA sequences with complex statistical patterns. This new stopping criterion is based on Bayesian information criterion in the model selection framework. When this criterion is applied to telomere of S. cerevisiae and the complete sequence of E. coli, borders of biologically meaningful units were identified, and a more ...

Stopping rules for ascending audiological test procedures were evaluated by Monte Carlo simulation. The stopping rules differed in the minimum number of responses required at a level, whether these responses occurred on half or a majority of the ascending series, and whether all or only the most recent ascending series were considered. For all procedures, shallow psychometric function slopes yi...

This paper proposes a new stopping criterion for automatic image segmentation based on region merging. The criterion is dependent on image content itself and when combined with the recently proposed approaches to syntactic segmentation can produce results aligned with the most salient semantic regions/objects present in the scene across heterogeneous image collections. The method identifies a s...

recently, in order to increase the efficiency of least squares method in numerical solution of ill-posed problems, the chain least squares method is presented in a recurrent process by babolian et al. despite the fact that the given method has many advantages in terms of accuracy and stability, it does not have any stopping criterion and has high computational cost. in this article, the attempt...

Cross validation can be used to detect when over tting starts during supervised training of a neural network; training is then stopped before convergence to avoid the overtting (\early stopping"). The exact criterion used for cross validation based early stopping, however, is chosen in an ad-hoc fashion by most researchers or training is stopped interactively. To aid a more well-founded selecti...