Abstract:
A Particle Swarm Optimization (PSO) technique, in conjunction with Fuzzy Adaptive Resonance Theory (ART), was implemented to adapt vigilance values to appropriately compe...Show MoreMetadata
Abstract:
A Particle Swarm Optimization (PSO) technique, in conjunction with Fuzzy Adaptive Resonance Theory (ART), was implemented to adapt vigilance values to appropriately compensate for a disparity in data sparsity. Gaining the ability to optimize a vigilance threshold over each cluster as it is created is useful because not all conceivable clusters have the same sparsity from the cluster centroid. Instead of selecting a single vigilance threshold, a metric must be selected for the PSO to optimize on. This trades one design decision for another. The performance gain, however, motivates the tradeoff in certain applications.
Date of Conference: 12-17 July 2015
Date Added to IEEE Xplore: 01 October 2015
ISBN Information: