Fuzzy Clustering with Obstructed Distance Based on Quantum-Behaved Particle Swarm Optimization
Lu Ping, Anxin Zhao · 2010
typical, partitioning, methods, of, constraint-based spatial, clustering, algorithms, are, based, on, gradient, descent, which are easily falling into local extremum and sensitive to the initial parameters. A new fuzzy clustering with detour distance algorithm, based, on, quantum-behaved, particle, swarm optimization, (QFCOD), was, proposed., The, new, spatial clustering, with, obstacles, constrained, algorithm, avoids, the fitness value of clustering falling into local extremum in a large degree., Furthermore, QFCOD, adopts, membership, grade, in the, object, function, of, QPSO, redefines, detour, distance, and applies, the, Particles, Escaping, Principle, to, avoiding, that, the updated, cluster, center, particle, sinking, into, the, area, of, the obstacles., Finally, this, algorithm, illustrates, effectiveness, and accuracy on the basis of the experiments running in the Matlab environment and the sample points with obstacles.