Name
Title | ||
|---|---|---|
Effective evaluation model under the condition of insufficient and uncertain information |
Abstract | ||
|---|---|---|
To evaluate various objects their appropriate levels is necessary to arrange reasonable resource. However, the problem of insufficient and uncertain information is often encountered in practice and makes evaluation complex. Therefore, this study develops the concepts of grey number and integrates them into the grey clustering technique to establish an improved evaluation model. An illustrative example of pavement condition evaluation has been adopted to demonstrate the feasibility and practicability of the proposed model. Results show that the proposed model is effective and robust, and quite good for real-world applications. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.eswa.2008.06.079 | Expert Syst. Appl. |
Keywords | Field | DocType |
grey clustering technique,improved evaluation model,uncertain information,evaluation complex,pavement condition evaluation,illustrative example,real-world application,grey number,evaluation model,appropriate level,insufficient,reasonable resource,effective evaluation model | Data mining,Condition evaluation,Grey clustering,Computer science,Artificial intelligence,Machine learning | Journal |
Volume | Issue | ISSN |
36 | 3 | Expert Systems With Applications |
Citations | PageRank | References |
3 | 0.49 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong-Huang Lin | 1 | 136 | 9.40 |
| Pin-Chan Lee | 2 | 75 | 6.26 |