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An important issue regarding the design of support vector machines (SVMs) is considered in this article, namely, the fine tuning of parameters in SVMs. This problem is tackled by using a self-adaptive genetic algorithm (GA). The same GA is used for feature selection. We validate our results implementing some statistical tests based on single domain benchmark data sets, which are used for comparison...
Learning how to count in different bases has been seen as a trivial task in almost all introductory mathematics courses. However, the low performance shown by many students, while performing this task, is appalling. This situation has motivated serious research in this matter. In order to study a model of count learning, we analyze the performance of a multilayer perceptron that learns to count in...
Scheduling of semiconductor wafer fabrication system is identified as a complex problem, involving multiple and conflicting objectives (makespan and minimizing waiting time for instance) to satisfy. In this study, we propose an effective approach based an artificial neural network technique embedded in a multi-objective optimization loop for multi-decision scheduling problems in a semiconductor wafer...
In this article we propose an effective method for a user-dependant voice command (small vocabulary) recognition system based on the combination of genetic algorithms and the Fisherpsilas linear discriminant ratio (FLDR). A genetic algorithm here is used to search in the frequency domain of the voice for those sub-bands whose energy is discriminant enough so as to distinguish between at least two...
The sustainability of the water uses in the future depends on the planning and the rational management of water resources. As many governments around the world, Brazil has endorsed in 1997 the federal law 9.433 on water resources, which previews the development of management tools to support decision making on how to use and regulate the rights of rational water use. This work presents a computational...
In multi-objective evolutionary optimization it is desirable to obtain a set of solutions usually called the Pareto optimal set. In this paper, some preliminary results are presented to approximate a Pareto optimal set considering an evolutionary adjustment of the parameters of a normal distribution function. The univariable and multivariable normal distribution functions are considered. Four test...
School timetabling is a hard task that educational centers have to perform regularly and which implies a large waste of time and human efforts. For such reason designing techniques for the automatic generation of timetables is still of interest. Even though many contributions exist, the characteristics of the problem vary depending on the school policies, the country (laws), and other particular variables...
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