Towards Autonomous Evolutionary Design Systems via Grid-Based Technologies

Parmee, I. C., Abraham, J., Shackelford, M., Rana, Omer Farooq ORCID: https://orcid.org/0000-0003-3597-2646 and Shaikh Ali, Ali 2005. Towards Autonomous Evolutionary Design Systems via Grid-Based Technologies. Presented at: International Conference on Computing in Civil Engineering, Cancun, Mexico, 12-15 July 2005. Published in: Soibelman, L. and Feniosky, P.-M. eds. Proceedings: Computing in Civil Engineering (2005). New York, NY: American Society of Civil Engineers, 10.1061/40794(179)118

Full text not available from this repository.

Abstract

The paper describes the initial development of the data modelling and search, exploration and optimisation processes (SEO) of a Grid-enabled problem solving environment (PSE). This environment will enable a client to access coupled computational components sited at different centres of expertise. Each centre offers a data generation and analysis approach that aids a better understanding of the design domain whilst providing a route to the identification of appropriate high-performance design solutions. The intention is to support satisfactory, remote problem definition that leads to the selection and application of appropriate design search, exploration and optimisation techniques. This should occur seamlessly so that the client is unaware that these processes are to be undertaken at different sites. The intention is that the system will support clients with extensive knowledge of their design domain but little expertise in state-of-the-art data modelling and SEO processes.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Uncontrolled Keywords:	Computation, Conceptual design, Data analysis, Grid systems, Conceptual Design, Data Modelling, Evolutionary Computing, Grid Computing
Publisher:	American Society of Civil Engineers
ISBN:	9780784407943
Last Modified:	24 Oct 2022 10:20
URI:	https://orca.cardiff.ac.uk/id/eprint/43927

Citation Data

Cited 9 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item