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Gravitational search algorithm (GSA) has gained increasing attention in dealing with complex optimization problems. Nevertheless it still has some drawbacks, such as slow convergence and the tendency to become trapped in local minima. Chaos generated by the logistic map, with the properties of ergodicity and stochasticity, has been used to combine with GSA to enhance its searching performance. In...
We consider the problem of synthesizing multiple valued logic (MVL) functions by neural networks. A differential evolution algorithm is proposed to train the learnable multiple valued logic network. The optimum window and biasing parameters to be chosen for convergence are derived. Experiments performed on benchmark problems demonstrate the convergence and robustness of the network. Preliminary results...
As a simple, effective and nonparametric classification method, k Nearest Neighbor (KNN) is widely used in document classification for dealing with the much more difficult problem such as large-scale or many of categories. But KNN classifier may have a problem when training samples are uneven. The problem is that KNN classifier may decrease the precision of classification because of the uneven density...
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