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Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/579204
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dc.contributor.authorIsmail S (UUM)
dc.contributor.authorZulkifli M (UUM)
dc.contributor.authorMansor R (UUM)
dc.contributor.authorMat Yusof M (UUM)
dc.contributor.authorIsmail M. I (UUM)
dc.date.accessioned2023-11-06T03:17:25Z-
dc.date.available2023-11-06T03:17:25Z-
dc.date.issued2016-10
dc.identifier.issn0128-7702
dc.identifier.otherukmvital:116523
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/579204-
dc.descriptionExploratory Data Analysis (EDA) is an approach introduced by Tukey. The aim is to obtain an in depth understanding of data using graphics. This contradicts the classical approach which uses statistical summaries such as mean and standard deviation among others. Skipping EDA in investigating data can jeopardise the validity and reliability of the results. In this study, we highlight the crucial role of EDA in electricity forecasting via line chart to understand the existence of the four-time series components i.e. trend, seasonal, irregular and cyclical. Daily electricity load for financial year 2002 to 2006 are used. The EDA showed irregular patterns identified in the line chart are not irregular components but moving seasonal components which require different techniques of forecasting.
dc.language.isoen
dc.publisherUniversiti Putra Malaysia Press
dc.relation.haspartPertanika Journals
dc.relation.urihttp://www.pertanika.upm.edu.my/view_archives.php?journal=JSSH-24-S-10
dc.rightsUKM
dc.subjectGraphical
dc.subjectClassical approach
dc.subjectTime series components
dc.subjectLine chart
dc.subjectMoving seasonal
dc.titleThe role of exploratory data analysis (eda) in electricity forecasting
dc.typeJournal Article
dc.format.volume24
dc.format.pages93-100
dc.format.issueSpecial Issue
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