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Prediction of Thermal Properties of Sweet Sorghum Bagasse as a Function of Moisture Content Using Artificial Neural Networks and Regression Models Cover

Prediction of Thermal Properties of Sweet Sorghum Bagasse as a Function of Moisture Content Using Artificial Neural Networks and Regression Models

Acta Technologica Agriculturae
Volume 20 (2017): Issue 2 (June 2017)
By: Ramana Gosukonda,  Ajit K. Mahapatra,  Daniel Ekefre and  Mark Latimore  
Open Access
|Jun 2017

Authors

Ramana Gosukonda

College of Agriculture, Family Sciences and Technology, Fort Valley State University,, Fort Valley, USA

Ajit K. Mahapatra

College of Agriculture, Family Sciences and Technology, Fort Valley State University,, Fort Valley, USA

Daniel Ekefre

College of Agriculture, Family Sciences and Technology, Fort Valley State University,, Fort Valley, USA

Mark Latimore

College of Agriculture, Family Sciences and Technology, Fort Valley State University,, Fort Valley, USA
DOI: https://doi.org/10.1515/ata-2017-0006 | Journal eISSN: 1338-5267
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Language: English
Page range: 29 - 35
Published on: Jun 23, 2017
Published by: Slovak University of Agriculture in Nitra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
ANN,
sweet sorghum bagasse,
moisture content,
thermal properties
Related subjects:
Engineering,
Introductions and overviews,
Engineering, other

© 2017 Ramana Gosukonda, Ajit K. Mahapatra, Daniel Ekefre, Mark Latimore, published by Slovak University of Agriculture in Nitra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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