Inverse Parameter Identification Technique Using PSO Algorithm Applied to Geotechnical Modeling. (4th May 2008)
- Record Type:
- Journal Article
- Title:
- Inverse Parameter Identification Technique Using PSO Algorithm Applied to Geotechnical Modeling. (4th May 2008)
- Main Title:
- Inverse Parameter Identification Technique Using PSO Algorithm Applied to Geotechnical Modeling
- Authors:
- Meier, Joerg
Schaedler, Winfried
Borgatti, Lisa
Corsini, Alessandro
Schanz, Tom - Other Names:
- Kennedy Jim Academic Editor.
- Abstract:
- Abstract : This paper presents a concept for the application of particle swarm optimization in geotechnical engineering. For the calculation of deformations in soil or rock, numerical simulations based on continuum methods are widely used. The material behavior is modeled using constitutive relations that require sets of material parameters to be specified. We present an inverse parameter identification technique, based on statistical analyses and a particle swarm optimization algorithm, to be used in the calibration process of geomechanical models. Its application is demonstrated with typical examples from the fields of soil mechanics and engineering geology. The results for two different laboratory tests and a natural slope clearly show that particle swarms are an efficient and fast tool for finding improved parameter sets to represent the measured reference data.
- Is Part Of:
- Journal of artificial evolution and applications. Volume 2008(2008)
- Journal:
- Journal of artificial evolution and applications
- Issue:
- Volume 2008(2008)
- Issue Display:
- Volume 2008, Issue 2008 (2008)
- Year:
- 2008
- Volume:
- 2008
- Issue:
- 2008
- Issue Sort Value:
- 2008-2008-2008-0000
- Page Start:
- Page End:
- Publication Date:
- 2008-05-04
- Subjects:
- Evolutionary programming (Computer science) -- Periodicals
Evolutionary programming (Computer science)
Periodicals
Electronic journals
006.3823 - Journal URLs:
- https://www.hindawi.com/journals/jaea/ ↗
- DOI:
- 10.1155/2008/574613 ↗
- Languages:
- English
- ISSNs:
- 1687-6229
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10827.xml