Predicting Performance of Briquette Made from Millet Bran: A Neural Network Approach

Advanced Journal of Graduate Research

View Publication Info
 
 
Field Value
 
Title Predicting Performance of Briquette Made from Millet Bran: A Neural Network Approach
 
Creator Kumar, Gaurav
Thampi B.S., Gireeshkumaran
Mondal, Pranab Kumar
 
Subject Biomass
Millet bran
Briquette
Artificial Neural Network
Multiple Linear Regression
 
Description Millet bran possesses good fuel quality and can be successfully used as a professional feedstock for producing solid biofuel.  In this paper, a framework for developing an Artificial Neural Network (ANN) to estimate the performance of millet bran briquettes is presented by using experimental data to train, test, and validate the ANN. With the capacity of the developed multi-layer ANN, the effects of moisture content, temperature, and applied pressure on the density, durability, and impact resistance are predicted. Different cases considering three parameters as inputs to the ANN, namely, moisture content, temperature, and applied pressure were analyzed. The outputs of the ANN are the density, durability, and impact resistance for each of the input parameters separately. By comparing with the experimental values, it is shown that the ANN-based method can predict the data well with a Mean Square Error (MSE) value ~ 0.2%. Further, Multiple Linear Regression (MLR) model is used to check the efficiency of ANN prediction from which it is shown that the proposed ANN-based method provides useful guidance for the prediction of the physical parameters efficiently, with the least deviation and high accuracy.
 
Publisher AIJR Publisher
 
Date 2020-09-21
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Graduate Research
 
Format application/pdf
 
Identifier https://journals.aijr.in/index.php/ajgr/article/view/2735
10.21467/ajgr.9.1.1-13
 
Source Advanced Journal of Graduate Research; Vol. 9 No. 1 (2021): January 2021; 1-13
2456-7108
10.21467/ajgr.9.1.2021
 
Language eng
 
Relation https://journals.aijr.in/index.php/ajgr/article/view/2735/338
 
Rights Copyright (c) 2020 Gaurav Kumar, Gireeshkumaran Thampi B.S., Pranab Kumar Mondal
http://creativecommons.org/licenses/by-nc/4.0
 

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us

Twitter

Copyright © 2015-2018 Simon Fraser University Library