Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
405347 | Knowledge-Based Systems | 2010 | 13 Pages |
Abstract
This paper suggests an original heuristic modelling algorithm expressed in terms of homogenous combinations of the classical system dynamics and the Bayesian degree of truth employed in modelling. The main benefits of the proposed approach compared to classical modelling are the increased transparency and alleviated computational time. Two case studies, dealing with a mobile robot and an unforced pendulum system, are included to exemplify and test the theoretical results. One of the case studies makes use of the definition and calculation of several discrete plausibilities.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Claudiu Pozna, Radu-Emil Precup, József K. Tar, Igor Škrjanc, Stefan Preitl,