Prediction of fuel usage consumption in the airline industry

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.advisorJuhasz, Bertalan
dc.contributor.authorFacchini, Stefano
dc.contributor.schoolPerustieteiden korkeakoulufi
dc.contributor.supervisorJung, Alexander
dc.date.accessioned2024-03-17T18:07:37Z
dc.date.available2024-03-17T18:07:37Z
dc.date.issued2024-03-11
dc.description.abstractThis document presents a study on the prediction of fuel usage consumption in the airline industry using machine learning methods. The research aims to apply and compare different machine learning models to real-world data on various factors that influence fuel consumption during flights. The models evaluated include linear regression, polynomial regression, neural network, decision tree, random forest, support vector machine, gradient boosting regression, and AdaBoost regression. The results show that some of the machine learning models, such as Random Forest and Gradient Boosting Regression, performed well on the prediction task, while others, such as Adaptive Boosting Regression, showed limitations and weaknesses. The study has implications for the airline industry, especially in terms of cost forecasting, efficiency optimization, and sustainability enhancement. The research is concluded by suggesting some possible directions for future research, such as incorporating more features, testing new models, and applying the models to different scenarios.en
dc.format.extent38
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/127102
dc.identifier.urnURN:NBN:fi:aalto-202403172740
dc.language.isoenen
dc.programmeMaster's Programme in ICT Innovationfi
dc.programme.majorData Sciencefi
dc.programme.mcodeSCI3115fi
dc.subject.keywordfuelen
dc.subject.keywordconsumptionen
dc.subject.keywordpredictionen
dc.subject.keywordusageen
dc.subject.keywordforecastingen
dc.titlePrediction of fuel usage consumption in the airline industryen
dc.typeG2 Pro gradu, diplomityöfi
dc.type.ontasotMaster's thesisen
dc.type.ontasotDiplomityöfi
local.aalto.electroniconlyyes
local.aalto.openaccessno
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