Name
Title | ||
|---|---|---|
Artificial neural network modelling of the bioethanol-to-olefins process on a HZSM-5 catalyst treated with alkali. |
Abstract | ||
|---|---|---|
•A bioethanol-to-olefin process has been modelled using artificial neural networks.•The model achieves similar fitness than a knowledge modelling approach.•Neural networks learn the process dynamics better than support vector machines. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.asoc.2017.05.006 | Applied Soft Computing |
Keywords | Field | DocType |
Prediction model,BTO process,Artificial neural networks | Mathematical optimization,Experimental data,Support vector machine,Automatic control,Artificial intelligence,Artificial neural network,Biorefinery,Mathematics,Bayesian interpretation of regularization,Machine learning | Journal |
Volume | ISSN | Citations |
58 | 1568-4946 | 2 |
PageRank | References | Authors |
0.36 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gorka Sorrosal | 1 | 2 | 0.70 |
| Eloy Irigoyen | 2 | 38 | 14.23 |
| Cruz E. Borges | 3 | 25 | 6.96 |
| Cristina Martin | 4 | 2 | 1.04 |
| Ana María Macarulla | 5 | 2 | 0.36 |
| Ainhoa Alonso-Vicario | 6 | 7 | 3.14 |