Energy content modelling for municipal solid waste using adaptive neuro-fuzzy inference system (anfis)

Oluwatobi Adeleke, Stephen A. Akinlabi, Paul A. Adedeji, Tien Chien Jen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Recovery of energy from municipal solid waste (MSW) will not only add to the national electrical energy generation capacity, but it will also minimize the quantity of waste that ends up in landfill, consequently mitigating its environmental impact. This study has developed ANFIS model to forecast the energy content of waste generated in Johannesburg, South Africa, based on the physical component of the waste: plastic, paper, organics, metals, and textile as input against the energy content. The fuzzy c-means (FCM) clustering technique was explored for data clustering in the ANFIS model. The model was trained with 70% of the data and 30% for validation. The performance of the network was evaluated using root mean square error (RMSE), mean absolute deviation (MAD), and mean absolute percentage error (MAPE). The RMSE, MAD, and MAPE of the model were 0.3418, 0.2692, and 7.7991, respectively. The forecast accuracy of ANFIS was compared with ANN, giving a MAPE of 7.7991 and 13.7870, respectively. ANFIS gave a better forecast accuracy and recommended for energy content prediction of municipal solid waste.

Original languageEnglish
Title of host publicationAdvances in Manufacturing Engineering - Selected Articles from ICMMPE 2019
EditorsSeyed Sattar Emamian, Farazila Yusof, Mokhtar Awang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages177-185
Number of pages9
ISBN (Print)9789811557521
DOIs
Publication statusPublished - 2020
Event5th International Conference on Mechanical, Manufacturing and Plant Engineering, ICMMPE 2019 - Kuala Lumpur, Malaysia
Duration: 19 Nov 201921 Nov 2019

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364

Conference

Conference5th International Conference on Mechanical, Manufacturing and Plant Engineering, ICMMPE 2019
Country/TerritoryMalaysia
CityKuala Lumpur
Period19/11/1921/11/19

Keywords

  • Adaptive neuro-fuzzy inference system
  • Municipal solid waste
  • Season

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes

Fingerprint

Dive into the research topics of 'Energy content modelling for municipal solid waste using adaptive neuro-fuzzy inference system (anfis)'. Together they form a unique fingerprint.

Cite this