Name
Title | ||
|---|---|---|
Using Classical and Evolutive Neural Models in Industrial Applications: A Case Study for an Automatic Coin Classifier |
Abstract | ||
|---|---|---|
In this paper we shall present a general methodology to be used when artificial neural network models are applied to solve real tasks in industrial environments. This methodology will be outlined by means of a case study which consists in the implementation of the decision/classification engine to be included in an automatic coin classifier. This coin classifier is incorporated in commercial vending machines, so that the problems arising when trying to face the conditions imposed by real environments have to be considered. The methodology presented in this paper can be considered as divided in three main tasks: database compilation and analysis, selection of the proper neural model and its implementation. A wide range of neural models, including classical as well as evolutive algorithms, has been considered. As the experimental results provided show, the use of artificial neural models for implementing the proposed classifier proves to overcome some of the limitations inherent to the traditional techniques considered when solving this task. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1007/BFb0032552 | IWANN |
Keywords | Field | DocType |
evolutive neural models,automatic coin classifier,case study,industrial applications,artificial neural network | Artificial neural network model,Physical neural network,Computer science,Probabilistic neural network,Time delay neural network,Artificial intelligence,Artificial neural network,Classifier (linguistics),Machine learning | Conference |
Volume | ISSN | ISBN |
1240 | 0302-9743 | 3-540-63047-3 |
Citations | PageRank | References |
2 | 0.41 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan Manuel Moreno | 1 | 186 | 32.74 |
| Jordi Madrenas | 2 | 150 | 27.87 |
| joan cabestany | 3 | 1276 | 143.82 |
| J. R. Laúna | 4 | 2 | 0.41 |