Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Use of artificial neural network models to derive particle size distributions and their moments from chord length distributions
Includes bibliographical references (leaves 121-123).
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Chemical Engineering
2014
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
Similar Items: Use of artificial neural network models to derive particle size distributions and their moments from chord length distributions
- Investigation into the effective lengths of web compression elements in parallel chord trusses
- Image-based prediction of particle size distribution in recycled stabilized soils using convolutional neural networks
- Particle size estimation of hydrocyclone overflow
- Derivation of nonstationary Lotka-type distributions without divergence of moments
- Investigation of the effect of particle size on froth stability
- Modelling of mass transfer operations with artificial neural networks