Name
Title | ||
|---|---|---|
Comparison Between Choquet And Sugeno Integrals As Aggregation Operators For Modular Neural Networks |
Abstract | ||
|---|---|---|
In this paper, a comparison of the Choquet and Sugeno integrals is presented. The proposed methods enable the calculation of the Choquet and Sugeno integrals for combining multiple source of information with a degree of uncertainty. The methods are used to combine the modules output of a modular neural network for face recognition. In this paper, the focus is on aggregation operators that use measures as inputs, in particular the Choquet and Sugeno integrals. Recognition results with the Choquet integral are better or comparable to results produced by Sugeno integral. |
Year | Venue | Keywords |
|---|---|---|
2016 | 2016 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE) | Aggregation operators, Choquet Integral, Sugeno integral, Modular Neural networks, fuzzy measures, fuzzy densities |
Field | DocType | ISSN |
Computer science,Sugeno integral,Fuzzy measure theory,Modular neural network,Artificial intelligence,Operator (computer programming),Choquet integral,Modular design,Fuzzy control system,Artificial neural network,Machine learning | Conference | 1544-5615 |
Citations | PageRank | References |
2 | 0.37 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gabriela E. Martinez | 1 | 19 | 2.57 |
| Olivia Mendoza | 2 | 365 | 21.73 |
| Patricia Melin | 3 | 4009 | 259.43 |
| Fernando Gaxiola | 4 | 135 | 8.42 |