๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Modelling the permeability of polymers: a neural network approach

โœ Scribed by M. Wessling; M.H.V. Mulder; A. Bos; M. van der Linden; M. Bos; W.E. van der Linden


Publisher
Elsevier Science
Year
1994
Tongue
English
Weight
451 KB
Volume
86
Category
Article
ISSN
0376-7388

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Modelling of abrasive flow machining pro
โœ R.K. Jain; V.K. Jain; P.K. Kalra ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 256 KB

A simple neural network model for abrasive flow machining process has been established. The effects of machining parameters on material removal rate and surface finish have been experimentally analysed. Based on this analysis, model inputs and outputs were chosen and off-line model training using ba

A neural network approach to prediction
โœ Xi Chen; Les Sztandera; Hugh M. Cartwright ๐Ÿ“‚ Article ๐Ÿ“… 2007 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 93 KB

Polymeric materials are finding increasing application in commercial optical communication systems. Taking advantage of techniques from the field of artificial intelligence, the goal of our research is to construct systems that can computationally design polymer formulations, including polymer optic

A neural network approach to forecasting
โœ Jeffrey E. Sohl; A.R. Venkatachalam ๐Ÿ“‚ Article ๐Ÿ“… 1995 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 482 KB

The literature has shown that no one model provides the most accurate forecasts. The focus has instead shifted to identifying the characteristics of the time series in order to provide guidelines for choosing the most appropriate extrapolation model. In this paper we test the feasibility of employin