We review here briefly some of our recent studies on neural network modelling. We discuss the studies on relaxation and growth of correlation in the Hopfield model, increase in memory loading capacity with an extended Hopfield-like model with delayed dynamics, the prediction capability of time serie
โฆ LIBER โฆ
Safety-modelling on neural networks
โ Scribed by Mamoun Suliman
- Publisher
- Elsevier Science
- Year
- 1991
- Tongue
- English
- Weight
- 332 KB
- Volume
- 31
- Category
- Article
- ISSN
- 0026-2714
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Modelling neural networks
โ
Bikas K. Chakrabarti; Prabir K. Dasgupta
๐
Article
๐
1992
๐
Elsevier Science
๐
English
โ 720 KB
Modelling of halomethanes using neural n
โ
Hiroshi Yoshida; Yoshikastu Miyashita; Shin-ich Sasaki
๐
Article
๐
1996
๐
Elsevier Science
๐
English
โ 642 KB
Modelling metabolic energy by neural net
โ
J. Lozano; M. Noviฤ; F.X. Rius; J. Zupan
๐
Article
๐
1995
๐
Elsevier Science
๐
English
โ 995 KB
ON MODEL UPDATING USING NEURAL NETWORKS
โ
M.J. Atalla; D.J. Inman
๐
Article
๐
1998
๐
Elsevier Science
๐
English
โ 340 KB
Markov availability models on neural net
โ
Mamoun Suliman; Charles A. Goben
๐
Article
๐
1992
๐
Elsevier Science
๐
English
โ 379 KB
Response models based on bagging neural
โ
Kyoungnam Ha; Sungzoon Cho; Douglas MacLachlan
๐
Article
๐
2005
๐
John Wiley and Sons
๐
English
โ 217 KB
Identifying customers who are likely to respond to a product offering is an important issue in direct marketing.Response models are typically built from historical purchase data. A popular method of choice, logistic regression, is easy to understand and build, but limited in that the model is linear