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Abstract: The Kalman Swarm (KSwarm) is a new approach to particle motion in PSO that reduces the number of iterations required to reach good solutions [1]. Unfortunately, it has much higher computational complexity than basic PSO. This paper addresses the runtime of KSwarm in a new algorithm called "Linear Kalman Swarm" (LinkSwarm) which has linear complexity and performs even better than KSwarm. Some possible reasons for the success of KSwarm are also explored. (Update)
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BibTeX entry: (Update)
@misc{ essential-improving,
author = "Extracting Its Essential",
title = "Improving on the Kalman Swarm",
url = "citeseer.ist.psu.edu/735650.html" }
Citations (may not include all citations):384 A new approach to linear filtering and prediction problems (context) - Kalman - 1960
36 Parameter selection in particle swarm optimization (context) - Shi, Eberhart - 1998 ACM DBLP
14 Empirical study of particle swarm optimization (context) - Shi, Eberhart - 1950
9 Using selection to improve particle swarm optimization (context) - Angeline - 1998
7 Particle swarm optimisation with spatial particle extension (context) - Krink, Vestertroem et al. - 2002
6 Population structure and particle swarm performance (context) - Kennedy, Mendes - 2002
6 Stereotyping: Improving particle swarm performance with clus.. (context) - Kennedy - 2000
5 Bare bones particle swarms (context) - Kennedy - 2003
5 Small worlds and mega-minds: E#ects of neighborhood topology.. (context) - Kennedy - 1938
4 Division of labor in particle swarm optimisation (context) - Vesterstroem, Riget et al. - 2002
4 Watch thy neighbor or how the swarm can learn from its envir.. (context) - Mendes, Kennedy et al. - 2003
3 Dynamic sociometry in particle swarm optimization (context) - Richards, Ventura - 2003
3 Neighborhood topologies in fully-informed and best-ofneighbo.. (context) - Kennedy, Mendes - 2003
2 A diversity-guided particle swarm optimizer -- the ARPSO (context) - Vesterstrm, Riget - 2002
1 The Kalman swarm (context) - Monson, Seppi - 2004
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