Name
Title | ||
|---|---|---|
Neuro-fuzzy inference system to learn expert decision: between performance and intelligibility |
Abstract | ||
|---|---|---|
We present a discrimation method for seismic events. One event is described by high level features. Since these variables are both quantitative and qualitative, we develop a processing line, on the cross-road of statistics (”Mixtures of Experts”) and Artificial Intelligence (”Fuzzy Inference System”). It can be viewed as an original extension of Radial Basis Function Networks. The method provides an efficient trade-off between high performance and intelligibility. We propose also a graphical presentation of the model satisfying the experts' requirements for intelligibility. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11540007_168 | FSKD (2) |
Keywords | Field | DocType |
artificial intelligence,high level feature,expert decision,efficient trade-off,neuro-fuzzy inference system,high performance,processing line,graphical presentation,original extension,radial basis function networks,fuzzy inference system,discrimation method,artificial intelligent,satisfiability,radial basis function network | Neuro-fuzzy,Radial basis function,Inference,Computer science,Fuzzy logic,Expert system,Artificial intelligence,Artificial neural network,Machine learning,Intelligibility (communication),Inference system | Conference |
Volume | ISSN | ISBN |
3614 | 0302-9743 | 3-540-28331-5 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laurence Cornez | 1 | 1 | 0.71 |
| Manuel Samuelides | 2 | 67 | 11.71 |
| Jean-Denis Muller | 3 | 3 | 1.82 |