Comparative analysis of the heating values of biomass based on Ga-ANFIS and PsO-ANFIS models

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

2 Citations (Scopus)

Abstract

This article applied a hybridized, adaptive neuro-fuzzy inference system ANFIS-genetic algorithm (GA-ANFIS) and ANFIS -Particle swarm optimization (PSO-ANFIS) to predict the HHV of biomass. The minimum input parameter for the prediction model is based on the proximate values of biomass which are fixed carbon (FC), ash content (A) and volatile matter (VM). The 214 data which cover a wide range of biomass classes were extracted from reliable literature for the training and testing of the models. The optimal results obtained based on each modelling algorithm were compared. The proposed algorithms were evaluated by statistical indices which are the Coefficient of Correlation (CC), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD) estimated at 0.9189, 1.2369,7.4575 and 1.3560 respectively for PSO-ANFIS and 0.9088, 1.1200, 6.3960, 0.8895 respectively for GA-ANFIS. The GA showed exceptional ability to generalize in term of MAPE though at the expense of lesser CC which is obtained in the case of PSO. The reported indices showed that PSO-ANFIS and GA-ANFIS could be applied as an approach to the prediction of HHV based on proximate analysis instead of lengthy experiment procedures.

Original languageEnglish
Title of host publicationASME 2019 Power Conference, POWER 2019
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791859100
DOIs
Publication statusPublished - 2019
EventASME 2019 Power Conference, POWER 2019 - Salt Lake City, United States
Duration: 15 Jul 201918 Jul 2019

Publication series

NameAmerican Society of Mechanical Engineers, Power Division (Publication) POWER
Volume2019-July

Conference

ConferenceASME 2019 Power Conference, POWER 2019
Country/TerritoryUnited States
CitySalt Lake City
Period15/07/1918/07/19

Keywords

  • Biomass
  • GA-ANFIS
  • HHV
  • PSO-ANFIS
  • Proximate analysis

ASJC Scopus subject areas

  • Mechanical Engineering
  • Energy Engineering and Power Technology

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