Development of multiple machine-learning computational techniques for optimization of heterogenous catalytic biodiesel production from waste vegetable oil: Development of multiple machine-learning computational techniques for optimization Kamal Abdelbasset, W, Elkholi, SM, Jade Catalan Opulencia, M, Diana, T, Su, CH, Alashwal, M, Zwawi, M, Algarni, M, Abdelrahman, A and Nguyen, Hoang Chinh 2022, Development of multiple machine-learning computational techniques for optimization of heterogenous catalytic biodiesel production from waste vegetable oil: Development of multiple machine-learning computational techniques for optimization, Arabian Journal of Chemistry, vol. 15, no. 6, pp. 1-10, doi: 10.1016/j.arabjc.2022.103843. Attached Files Name Description MIMEType Size Downloads Title Development of multiple machine-learning computational techniques for optimization of heterogenous catalytic biodiesel production from waste vegetable oil: Development of multiple machine-learning computational techniques for optimization Author(s) Kamal Abdelbasset, W Elkholi, SM Jade Catalan Opulencia, M Diana, T Su, CH Alashwal, M Zwawi, M Algarni, M Abdelrahman, A Nguyen, Hoang Chinh Journal name Arabian Journal of Chemistry Volume number 15 Issue number 6 Article ID 103843 Start page 1 End page 10 Total pages 10 Publisher Elsevier Place of publication Amsterdam, The Netherlands Publication date 2022-06 ISSN 1878-5352 Keyword(s) Biodiesel Esterification Renewable energy Language eng DOI 10.1016/j.arabjc.2022.103843 Indigenous content off Field of Research 03 Chemical Sciences HERDC Research category C1 Refereed article in a scholarly journal Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30168503 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Life and Environmental Sciences Open Access Collection Related Links Link Description Link to full text (Open Access) Go to link with your DU access privileges   Connect to Elements publication management system Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Wed, 18 May 2022, 11:53:04 EST Wed, 18 May 2022, 16:31:17 EST Wed, 18 May 2022, 16:41:18 EST Tue, 26 Jul 2022, 15:57:39 EST Thu, 28 Jul 2022, 13:30:30 EST Thu, 28 Jul 2022, 14:02:03 EST Thu, 28 Jul 2022, 14:07:23 EST Thu, 28 Jul 2022, 14:14:33 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 6 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Wed, 18 May 2022, 11:53:04 EST