Name
Abstract | ||
|---|---|---|
Clavier, a case-based reasoning system that determines the placement of parts made of composite materials in an autoclave, is described. The heating rate of all parts put in an autoclave must be controlled carefully, but their number, shape, and placement can cause significant nonlocal variations. Clavier provides interactive support, using cases to propose load configurations and multiload plans. One of its advantages is that it learns, becoming more competent as it acquires new cases. Clavier's structure and results from evaluations of Clavier as an application and as a case-based reasoning research tool are discussed.<> |
Year | DOI | Venue |
|---|---|---|
1992 | 10.1109/64.163669 | IEEE Expert |
Keywords | Field | DocType |
case-based reasoning,convection,learning (artificial intelligence),materials science,physics computing,Clavier,autoclave,case-based reasoning research tool,case-based reasoning system,composite materials,interactive support,learns,load configurations,multiload plans,nonlocal variations | Data mining,Engineering drawing,Computer science,Artificial intelligence,Autoclave,Case-based reasoning,Reasoning system | Journal |
Volume | Issue | ISSN |
7 | 5 | 0885-9000 |
Citations | PageRank | References |
55 | 11.93 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel N. Hennessy | 1 | 55 | 11.93 |
| David Hinkle | 2 | 107 | 29.15 |