Name
Abstract | ||
|---|---|---|
Based on input and output relationship of qualitative mapping (QM), the attribute computing network model has been created. It brings forward a kind of computing method using input to adjust qualitative benchmark of attribute network, which makes it possible to achieve pattern recognition. Now the new attribute computing network model combined pattern recognition with synthetic evaluation is established. Firstly qualitative benchmarks of indexes are gotten by boundary study, and then by way of marking, preference for indexes is obtained, and lastly a set of satisfactory degrees for indexes is computed and outputted in descending sequence which ameliorates the effect of old satisfactory degree. Finally the simulation experiment is carried out to validate the theoretical model. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/GRC.2009.5255044 | GrC |
Keywords | DocType | ISBN |
attribute computing network,pattern recognition,the attribute computing network,qualitative mapping,synthetic evaluation method,boundary study,decision theory,synthetic evaluation,satisfactory degree function,computational modeling,data models,benchmark testing,indexes,data mining,indexation,simulation experiment,computer network | Conference | 978-1-4244-4830-2 |
Citations | PageRank | References |
3 | 0.57 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaolin Xu | 1 | 268 | 25.21 |
| Guanglin Xu | 2 | 26 | 9.95 |
| Jiali Feng | 3 | 31 | 11.84 |