KEDS: a knowledge-based equation discovery system for engineering problems

Author

Rao, R. Bharat ; Lu, Stephen C -Y

Author_Institution

Illinois Univ., Urbana, IL, USA

fYear

1992

fDate

2-6 Mar 1992

Firstpage

211

Lastpage

217

Abstract

Many engineering phenomena of interest are characterized by non-homogeneity. The authors discuss how the intertwining of the partitioning and discovery processes enables KEDS to learn relationships from engineering data and to extract the structure underlying these relationships. They present the KEDS algorithm and discuss the interaction between the two discovery and partitioning phases. Some extensions to the basic algorithm are described that greatly improve the performance of KEDS and increase the representation power of the models by permitting a probabilistic partitioning of the problem space. The results from running the KEDS system on data from a simulator for an internal combustion engine are presented

Keywords

combustion; engineering computing; knowledge based systems; learning (artificial intelligence); probabilistic logic; KEDS algorithm; discovery; engineering problems; internal combustion engine; knowledge-based equation discovery system; probabilistic partitioning; simulator; Buildings; Data engineering; Design engineering; Equations; Knowledge based systems; Knowledge engineering; Machine learning; Marine vehicles; Partitioning algorithms; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence for Applications, 1992., Proceedings of the Eighth Conference on

Conference_Location

Monterey, CA

Print_ISBN

0-8186-2690-9

Type

conf

DOI

10.1109/CAIA.1992.200032

Filename

200032