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AMC
2007
154views more  AMC 2007»
13 years 11 months ago
A hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training
The particle swarm optimization algorithm was showed to converge rapidly during the initial stages of a global search, but around global optimum, the search process will become ve...
Jing-Ru Zhang, Jun Zhang, Tat-Ming Lok, Michael R....
BMCBI
2006
146views more  BMCBI 2006»
13 years 11 months ago
Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influen...
Michael Meissner, Michael Schmuker, Gisbert Schnei...
CEC
2009
IEEE
14 years 6 months ago
Dynamic search initialisation strategies for multi-objective optimisation in peer-to-peer networks
Abstract— Peer-to-peer based distributed computing environments can be expected to be dynamic to greater of lesser degree. While node losses will not usually lead to catastrophic...
Ian Scriven, Andrew Lewis, Sanaz Mostaghim
RAS
2010
108views more  RAS 2010»
13 years 9 months ago
Swarm-supported outdoor localization with sparse visual data
— The localization of mobile systems with video data is a challenging field in robotic vision research. Apart from artificial environmental support technologies like GPS locali...
Marcel Kronfeld, Christian Weiss, Andreas Zell
SEMWEB
2009
Springer
14 years 5 months ago
MapPSO Results for OAEI 2009
Abstract. This paper presents and discusses the results of the latest developments of the MapPSO system, which is an ontology alignment approach that is based on discrete particle ...
Jürgen Bock, Peng Liu 0002, Jan Hettenhausen