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Contraposing mental task recognition, a novel Small-World neural network (SWNN) algorithm is proposed for the EEG classification tasks trying to solving the target hitting problem with the low spatial dispersion degree. A BMIs experimental paradigm with a series of Cue Scenes which focus on three-dimensional (3D) object control is described. Bring in the Small-World neural network, which is transformed...
To improve the intelligibility and efficiency of knowledge expression for the land evaluation, a land evaluation method combining simplified fuzzy classification association rules with fuzzy decision is proposed in this paper. To reduce the complexity of the land evaluation models and improve the efficiency and intelligibility of fuzzy classification association rules further, an algorithm to eliminate...
This paper proposed a novel multi-objective affinity set (MO affinity set) classification system comparing with ant colony optimization (ACO) and affinity set theory on delayed diagnosis dataset classification. The output of MO affinity set classification rules has the higher accuracy than ACO and traditional affinity set. Furthermore, our MO affinity set classification skips the traditional affinity...
In order to construct intelligible and effective land evaluation classifier, a semi-supervised learning algorithm constructed by utilizing simplified association rules combining with k-mean clustering algorithm is proposed in this paper. To reduce the complexity of the land evaluation models and improve the efficiency and intelligibility of association rules further, an algorithm to eliminate redundant...
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