Optimization of an algae ball mill grinder using artificial neural network

Arvin H. Fernando, Archie B. Maglaya, Aristotle Tulagan Ubando

研究成果: Conference contribution

摘要

Effects of the various ball mill operational grinding parameters for extracting microalgae were evaluated. This paper presents the use of MATLAB artificial neural network (ANN) for optimizing and improving the micro algae ball mill grinding process configuration set-up particularly on Nannochloropsis sp. The input parameters that was gathered, used and analyse are critical speed, duration, ball material, ball diameter, jar diameter, load percentage and ball-algae ratio. The researcher determines the amount of protein in the sample by using the Bradford Protein Assay Analysis. A total of 42 datasets was used to predict the optimize combination of the dataset. The authors used the MATLAB Programming and trained the neural network. MATLAB is used as an optimization tool to determine the best ball mill grinding configuration for the prototype set-up.

原文English
主出版物標題Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016
發行者Institute of Electrical and Electronics Engineers Inc.
頁面3752-3756
頁數5
ISBN(電子)9781509025961
DOIs
出版狀態Published - 2017 2月 8
事件2016 IEEE Region 10 Conference, TENCON 2016 - Singapore, Singapore
持續時間: 2016 11月 222016 11月 25

出版系列

名字IEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN(列印)2159-3442
ISSN(電子)2159-3450

Other

Other2016 IEEE Region 10 Conference, TENCON 2016
國家/地區Singapore
城市Singapore
期間16-11-2216-11-25

All Science Journal Classification (ASJC) codes

  • 電腦科學應用
  • 電氣與電子工程

指紋

深入研究「Optimization of an algae ball mill grinder using artificial neural network」主題。共同形成了獨特的指紋。

引用此