This slide presentation outlines information on learning from past experiences even for
advanced processes such as microfiltration (MF)/ultrafiltration (UF)
using artificial neural networks and use
that knowledge to predict future
performance. Topics covered include: basics of artificial neural networks (ANN); analogy to brain; typical ANN and one with more hidden layers; ANN application requirements; application to MF/UF; feed water turbidity and temperature; input and output parameters; training data; data used for training; ANN program; prediction vs. actual data; effect of temperature; relative importance: and, W/ & W/O temperature correction. Includes figures.
| Edition : | Vol. - No. |
| File Size : | 1
file
, 2.4 MB |
| Note : | This product is unavailable in Ukraine, Russia, Belarus |
| Number of Pages : | 27 |
| Published : | 03/01/2005 |
