Name
Abstract | ||
|---|---|---|
The theories and methods of performance evaluation for multi-sensor data fusion system based on rough set theory and a fuzzy interval are discussed. A information fusion performance criteria system is founded with C3I applications as background, the evaluation process is similar to the decision process. A function gj(a) represents an evaluation of object a for attribute j and is called a criteria. Each criterion induces a particular ordering of the object, and it is very significant to find a procedure by which to construct one overall preference ordering. Proposing the idea of translating imprecision or ambiguity in measurement of an alternative for a given point of view with the use of a fuzzy set in R which is a set of ordered pairs {x,muj a(x)} where muj a(x) is termed "the grade of membership of x" for alternative a related to j. This offered theoretical foundation for aggregation based on all evaluations from attributes. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/SNPD.2007.386 | SNPD (1) |
Keywords | Field | DocType |
rough set theory,function g,fuzzy set theory,fuzzy set,military computing,decision process,evaluation process,attribute j,information fusion performance criterion,multisensor data fusion system,decision theory,information fusion performance criteria system,performance evaluation,fuzzy interval,multi-sensor data fusion system,information fusion evaluation methodology,sensor fusion,dominance relation | Computer science,Fuzzy logic,Ordered pair,Rough set,Sensor fusion,Fuzzy set,Artificial intelligence,Decision theory,Information fusion,Ambiguity,Machine learning | Conference |
Volume | ISBN | Citations |
1 | 978-0-7695-2909-7 | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yunxiang Liu | 1 | 35 | 7.40 |
| Weichang Wu | 2 | 4 | 2.45 |
| Jie Lin | 3 | 3495 | 502.80 |