Prove d'ingresso e prestazione universitaria: una rete neurale per scienze motorie

Journal title DiPAV - QUADERNI
Author/s Giuseppe Favretto, Margherita Pasini, Orietta Nicolis
Publishing Year 2003 Issue 2002/4
Language Italian Pages 13 P. File size 327 KB
DOI
DOI is like a bar code for intellectual property: to have more infomation click here

Below, you can see the article first page

If you want to buy this article in PDF format, you can do it, following the instructions to buy download credits

Article preview

FrancoAngeli is member of Publishers International Linking Association, Inc (PILA), a not-for-profit association which run the CrossRef service enabling links to and from online scholarly content.

Among the statistical technique utilized by the Centro Docimologico to as-sess the validity of the selection tools of the students entering university, there are also the connessionist models, the neural networks. One of the main aims of the neural networks is to estimate the parameters of a nonlin-ear regression model. The neural model, after a first step of training by means of a set of patterns, is able to forecast the new values (generaliza-tion). In this work we relationed the students’ academic performance, reg-istered in Motor Sciences study course, with the results they achieved dur-ing the selection test using a multilayer feedforward neural network. The forecasting skill of the model has checked using some patterns we previ-ously excluded from the training sample.

Giuseppe Favretto, Margherita Pasini, Orietta Nicolis, Prove d'ingresso e prestazione universitaria: una rete neurale per scienze motorie in "DiPAV - QUADERNI" 4/2002, pp , DOI: