Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Microwave irradiation pretreatment and peroxyacetic acid desulfurization of coal and application of GRNN simultaneous predictor
Department of Mining Engineering, Science and Research Branch, Islamic Azad University, Iran.ORCID iD: 0000-0002-2265-6321
Department of Mining Engineering, Science and Research Branch,Islamic Azad University.
2011 (English)In: Fuel, ISSN 0016-2361, Vol. 90, no 11, p. 3156-3163Article in journal (Refereed) Published
Abstract [en]

Artificial neural network was used to predict the effects of operational parameters on coal desulfurization using peroxyacetic acid from microwave pretreated coal. Coal particle size (150–1125 μm), leaching temperature (25–85 °C), leaching time (0–120 min), microwave irradiation power (0–1000 W) and time (0–110 s) were used as inputs to the network. The outputs of the model were organic and inorganic sulfur reductions for 40 of the data sets. The GRNN artificial neural network with spread of 0.3 was used to estimate both organic and inorganic sulfur reduction from a combined database, which was established from microwave pretreatment and leaching experiments. Thirty-two data sets were used for training and eight data sets for testing. Simulated values obtained from the neural network, correspond closely to the experimental results. Satisfactory correlations of R2 = 0.99 and 0.97 were achieved during the testing stages of the prediction of inorganic and organic sulfur reductions respectively.

Place, publisher, year, edition, pages
Elsevier, 2011. Vol. 90, no 11, p. 3156-3163
Keywords [en]
Neural networks, Coal, Leaching
National Category
Mineral and Mine Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-72288DOI: 10.1016/j.fuel.2011.06.045ISI: 000295734200003Scopus ID: 2-s2.0-80052749314OAI: oai:DiVA.org:ltu-72288DiVA, id: diva2:1272021
Available from: 2018-12-18 Created: 2018-12-18 Last updated: 2019-02-25

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Chelgani, Saeed Chehreh

Search in DiVA

By author/editor
Chelgani, Saeed Chehreh
Mineral and Mine Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 175 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf