Use of an Artificial Neural Network to Evaluate the Oleo-Flotation Process to Treat Coal Fines
IR@CIMFR: CSIR-Central Institute of Mining and Fuel Research, Dhanbad
View Archive Info| Field | Value | |
| Title |
Use of an Artificial Neural Network to Evaluate the Oleo-Flotation Process to Treat Coal Fines
|
|
| Creator |
Charan, T. Gouri
Kalyani, V.K. Kumar, Lalan Sinha, A. |
|
| Subject |
Fuel Scinece
|
|
| Description |
The results of beneficiation studies of high-ash fine coal using the Oleo-flotation process are presented. The influence of three key variables (diesel oil dosage, wash oil [a product of crude oil obtained during the process of refining at 275 to 300 C] dosage, and impeller speed) of the Oleo- flotation process on yield % and ash % is presented in this article. An attempt is made to develop a three-layer feed-forward artificial-neural-network (ANN) model based on the experimental data set, which was trained using an error-back-propagation algorithm. The results indicated that the predictions from the ANN model are in good qualitative and quantitative agreement with the experimental observations, thereby validating the applicability and accuracy of the developed ANN model.
|
|
| Publisher |
Taylor & Francis
|
|
| Date |
2014
|
|
| Type |
Article
PeerReviewed |
|
| Format |
application/pdf
|
|
| Identifier |
http://cimfr.csircentral.net/1691/1/Use%20of.pdf
Charan, T. Gouri and Kalyani, V.K. and Kumar, Lalan and Sinha, A. (2014) Use of an Artificial Neural Network to Evaluate the Oleo-Flotation Process to Treat Coal Fines. International Journal of Coal Preparation and Utilization, 34. pp. 229-238. ISSN 1939-2699 |
|
| Relation |
http://DOI: 10.1080/19392699.2013.869585
http://cimfr.csircentral.net/1691/ |
|