Name
Abstract | ||
|---|---|---|
For complex systems and some new technology fields, simply rely on machines learning, the results are not reliable. Absorb the expert knowledge, will help us to more accurately grasp the status and the development of the complex or new fields. This paper presents a novel reduction algorithm that takes into account the knowledge of experts. The attributes set is divided into two subset according to the scores of the expert knowledge: the set of attributes with decisive expert knowledge and the set of attributes with experts' knowledge for reference, then a novel man-machine cooperative intelligent reduction algorithm (IRAEK, Intelligent Reduction Algorithm based on Expert Knowledge) is proposed to find the minimum reduction based on the different scores of expert knowledge. Finally, the empirical analysis result on the Micro-electromechanical Systems (MEMS) field shows that the IRAEK algorithm is feasible and efficient. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICESS.2009.45 | ICESS |
Keywords | Field | DocType |
iraek algorithm,cooperative intelligent reduction algorithm,complex system,minimum reduction,novel reduction algorithm,novel man-machine,new field,expert knowledge,new technology field,decisive expert knowledge,microelectromechanical systems,strontium,embedded software,machine learning,probability density function,data mining,algorithm design and analysis,information systems,knowledge management,learning artificial intelligence,financial management,expert systems,set theory,rough set theory | Information system,Algorithm design,Computer science,Subject-matter expert,Expert system,Algorithm,Knowledge-based systems,Rough set,Artificial intelligence,Knowledge base,Machine learning,Legal expert system | Conference |
ISSN | Citations | PageRank |
2576-3504 | 0 | 0.34 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junpeng Yuan | 1 | 17 | 2.15 |
| Jie Su | 2 | 0 | 0.68 |
| Cheng Su | 3 | 48 | 6.76 |