An adaptive neuro-fuzzy inference system for forecasting Australia's domestic low cost carrier passenger demand

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dc.contributor.authorPanarat Srisaeng
dc.contributor.authorGlenn Baxter
dc.contributor.authorGraham Wild
dc.date.accessioned2025-04-10T03:16:35Z
dc.date.available2025-04-10T03:16:35Z
dc.date.issued2015-07-03
dc.description.abstractThis study has proposed and empirically tested two Adaptive Neuro-Fuzzy Inference System (ANFIS) models for the first time for predicting Australia's domestic low cost carriers demand, as measured by enplaned passengers (PAX Model) and revenue passenger kilometres performed (RPKs Model). In the ANFIS, both the learning capabilities of an artificial neural network (ANN) and the reasoning capabilities of fuzzy logic are combined to provide enhanced prediction capabilities, as compared to using a single methodology. Sugeno fuzzy rules were used in the ANFIS structure and the Gaussian membership function and linear membership functions were also developed. The hybrid learning algorithm and the subtractive clustering partition method were used to generate the optimum ANFIS models. Data was normalized in order to increase the model's training performance. The results found that the mean absolute percentage error (MAPE) for the overall data set of the PAX and RPKs models was 1.52% and 1.17%, respectively. The highest R2-value for the PAX model was 0.9949 and 0.9953 for the RPKs model, demonstrating that the models have high predictive capabilities. © 2015 Vilnius Gediminas Technical University (VGTU) Press.
dc.identifier.doi10.3846/16487788.2015.1104806
dc.identifier.issn16487788
dc.identifier.urihttps://repository.dusit.ac.th//handle/123456789/6097
dc.language.isoen
dc.publisherTaylor and Francis Ltd.
dc.relation.ispartofseriesVolume 19, Issue 3; Pages 150 - 163
dc.subjectadaptive neuro-fuzzy inference system (ANFIS);
dc.subjectair transport
dc.subjectAustralia
dc.subjectforecasting methods
dc.subjectow cost carriers
dc.titleAn adaptive neuro-fuzzy inference system for forecasting Australia's domestic low cost carrier passenger demand
dc.typeArticle
mods.location.urlhttps://www.scopus.com/record/display.uri?eid=2-s2.0-84947063341&origin=resultslist&sort=plf-f&src=s&sid=8647c52412ef355555285f5a0877e45f&sot=anl&sdt=aut&s=AU-ID%28%22Srisaeng%2C+Panarat%22+56578825400%29&sl=38&sessionSearchId=8647c52412ef355555285f5a0877e45f&relpos=20
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