USING THE BOX-JENKINS METHOD IN TIME SERIES TO PREDICT THE MONTHLY ELECTRICAL LOADS IN (BABYLON GOVERNORATE - SHOMALI DISTRICT)

H. Mohammed, Ali Kazim Jari, W. S. Khudair
{"title":"USING THE BOX-JENKINS METHOD IN TIME SERIES TO PREDICT THE MONTHLY ELECTRICAL LOADS IN (BABYLON GOVERNORATE - SHOMALI DISTRICT)","authors":"H. Mohammed, Ali Kazim Jari, W. S. Khudair","doi":"10.24297/jam.v23i.9576","DOIUrl":null,"url":null,"abstract":"The topic of time series analysis is considered one of the important statistical topics to explain the phenomena that occur during a specific period of time. Time sequence examination objects to find an accurate account of the sequence, build a suitable perfect to interpret its behavior, and use the effects to predict the future time series . We using the Box-Jenkins method in the period sequence to predict the monthly electrical loads in (Babylon Governorate - Shomali district), and we have found that the studied time series is unstable in the mean and variance, we note that the time series is stable in the nasty and alteration. Autocorrelation and incomplete autocorrelation coefficients are used for the original data. Through these coefficients, we conclude that the appropriate model for the data is (3-1-2) ARMA. This model was chosen as it obtained the least (ARAM), and thus the model is appropriate for the data and the use of predictive values until the year (2022).","PeriodicalId":502930,"journal":{"name":"JOURNAL OF ADVANCES IN MATHEMATICS","volume":"56 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOURNAL OF ADVANCES IN MATHEMATICS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24297/jam.v23i.9576","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The topic of time series analysis is considered one of the important statistical topics to explain the phenomena that occur during a specific period of time. Time sequence examination objects to find an accurate account of the sequence, build a suitable perfect to interpret its behavior, and use the effects to predict the future time series . We using the Box-Jenkins method in the period sequence to predict the monthly electrical loads in (Babylon Governorate - Shomali district), and we have found that the studied time series is unstable in the mean and variance, we note that the time series is stable in the nasty and alteration. Autocorrelation and incomplete autocorrelation coefficients are used for the original data. Through these coefficients, we conclude that the appropriate model for the data is (3-1-2) ARMA. This model was chosen as it obtained the least (ARAM), and thus the model is appropriate for the data and the use of predictive values until the year (2022).
在时间序列中使用方框-詹金斯方法预测(巴比伦省 - 肖马里地区)的月度电力负荷
时间序列分析被认为是解释特定时间段内发生的现象的重要统计课题之一。时间序列检验的对象是找到序列的准确描述,建立一个合适的完美解释其行为的方法,并利用其效果来预测未来的时间序列。我们使用 Box-Jenkins 方法中的周期序列来预测(巴比伦省 - Shomali 区)的月度电力负荷,我们发现所研究的时间序列在均值和方差方面不稳定,我们注意到时间序列在下流和变化方面是稳定的。对原始数据使用了自相关系数和不完全自相关系数。通过这些系数,我们得出结论,数据的合适模型是(3-1-2)ARMA。选择该模型是因为它获得的(ARAM)最少,因此该模型适合数据和使用预测值,直到(2022 年)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信