Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/147902
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dc.contributor.authorSaini, Aditien_US
dc.date.accessioned2021-04-16T06:06:40Z-
dc.date.available2021-04-16T06:06:40Z-
dc.date.issued2021-
dc.identifier.citationSaini, A. (2021). Predictive analytics of chemical material pricing. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/147902en_US
dc.identifier.urihttps://hdl.handle.net/10356/147902-
dc.description.abstractPredictive analytics is the use of data, mathematical models and statistical algorithms to make predictions of the likelihood of future events. With the recent trend in technology and the ever-growing database of information, predictive analytics has become a catalyst to drive strategic decision making in most businesses today. This project explores the prediction of the prices of different raw material using time series- based analysis. Each raw material is composed of different chemicals, referred to as feedstocks. We investigate univariate and multivariate time series modelling techniques to create a generalised prediction pipeline using autocorrelation and cross-correlation analysis. We show through experiments and with the help of metrics (i.e., Mean Absolute Error and Mean Absolute Prediction Error) that how a statistical machine learning model outperforms the existing rule-based prediction model by identifying the underlying trends through correlation and time lag analysis.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Artificial intelligenceen_US
dc.titlePredictive analytics of chemical material pricingen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorZhang, Jieen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
dc.contributor.supervisor2Marcus De Carvalhoen_US
dc.contributor.supervisoremailZhangJ@ntu.edu.sgen_US
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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