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Traditional gene selection methods for microarray data mainly considered the features’ relevance by evaluating their utility for achieving accurate predication or exploiting data variance and distribution, and the selected genes were usually poorly explicable. To improve the interpretability of the selected genes as well as prediction accuracy, an improved gene selection method based on binary particle...
This paper proposes a novel approach of developing a vision-based forward collision warning system (V-FCW) under an integrated platform with both V-FCW algorithm development and field-test data driven system verification. The developed verification platform provides huge amount of video data collected from field testing under various real driving conditions with labeled ground truth and fast search...
In this paper, an improved particle swarm optimization (PSO) with the improved diversity is proposed to train feedforward neural networks (FNN). In this algorithm, first, the PSO algorithm is used to train the FNN. Second, when the particle swarm is trapped into local minima or loses its diversity, each particle in the swarm and its best position (Pb) are interrupted by a random function in order...
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