We consider the output of a simulation model of a system about which little is initially known. This output is often dependent on a large number of factors. It is helpful, in exam...
In this paper we describe a methodology that includes the complementary use of simulated annealing and response surface methodology (RSM). The methodology was developed for analys...
—This paper presents methodologies to select equities based on soft-computing models which focus on applying fundamental analysis for equities screening. This paper compares the ...
Estimating the generalization error is one of the key ingredients of supervised learning since a good generalization error estimator can be used for model selection. An unbiased g...
Abstract. In Computational Neuroscience, mathematical and computational modeling are differentiated. In this paper, both kinds of modeling are considered. In particular, modeling ...