Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):

C. Hametner, S. Jakubek:
"Comparison of EM Algorithm and Particle Swarm Optimisation for Local Model Network Training";
Vortrag: 2010 IEEE Conference on Cybernetics and Intelligent Systems (CIS), Singapur; 28.06.2010 - 30.06.2010; in: "Proceedings of the 2010 IEEE Conference on Cybernetics and Intelligent Systems (CIS)", (2010), 6 S.

Kurzfassung englisch:
Local model networks (LMNs) offer a versatile
structure for the identification of nonlinear static and dynamic
systems. In this paper an algorithm for the construction of a
tree-structured LMN with axis-oblique partitioning using particle
swarm optimisation (PSO) is presented. The PSO algorithm
allows the optimisation of arbitrary performance criteria but
is only used for a certain subtask which helps to reduce the
search space for the evolutionary algorithm very effectively. A
comparison using an Expectation-Maximisation (EM) algorithm
is presented. The differences and advantages of the LMN with
PSO and the EM algorithm, respectively, are highlighted by
means of an illustrative example. The practical applicability of the
proposed LMN with particle swarm optimisation is demonstrated
using real measurement data of an internal combustion engine.

Local model network, particle swarm optimisation, Expectation-Maximisation

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