ANALYZING END OF LIFE TYRE (ELT) CARBONS USING MACHINE LEARNING ALGORITHM
Author(s):
Aruna Sudame, Azza Al-Ghamdi, Ubio Obu, Jaiyeyemi Adekunle
Keywords:
carbon, End of life tyres(ELT), tyre waste, machine learning
Abstract
Waste tyre constitute a large percentage of wastes that affect the ecosystem. With an approximation of 1.5 billion tyres reaching their end of life every year, it is important to critically understand what constitutes waste tyres. End of life tyres commonly called ELT has given researchers lot of concerns with understanding it, how it operates and how to better recycle it. This paper is one of such contribution to help with understanding the compositions of ELT tyres but specifically on different carbons produced from ELT tyres. Obviously carbon is the most dominant and useful remnant of such waste, but In this paper we examined 3 types of end of life tyre carbon, namely IB 550A, IB 330B and IB 660C and their characteristics. We used Machine learning Algorithms to differentiate these carbons base on their chemical composition, to understand all the constituents. This study gives insight on different carbons derived from waste tyres and its composition. It furnishes us with information on the future utility of waste tyres based on the class of carbon it falls under based on our machine learning clustering model and the best utility for each class. With most studies on waste tyres using chemical processes and methodologies to understand waste tyres carbon, a machine learning approach introduces an entirely new approach.
Article Details
Unique Paper ID: 156860

Publication Volume & Issue: Volume 9, Issue 5

Page(s): 507 - 513
Article Preview & Download


Share This Article

Conference Alert

NCSST-2023

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2023

SWEC- Management

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2023

Go To Issue



Call For Paper

Volume 10 Issue 1

Last Date for paper submitting for March Issue is 25 June 2023

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews