COVID-19 Confirmed Cases Forecasting in Malaysia Using Linear Regression and Holt's Winter Algorithm

IF 0.4 Q4 ENGINEERING, MULTIDISCIPLINARY

International Journal of Integrated Engineering Pub Date : 2023-07-31 DOI:10.30880/ijie.2023.15.03.006

H. Hasri, Siti Armiza Mohd Aris, Robiah Ahmad, Celia Shahnaz

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引用次数: 0

Abstract

The 2019 coronavirus disease pandemic (COVID-19)has emerged and is spreading rapidly over the world.Therefore, it may be highly significantto have the general population tested for COVID-19. There has been a rapid surge in the use of machine learning to combat COVID-19 in the past few years, owing to its ability to scale up quickly, its higher processing power, and the fact that it is more trustworthy than peoplein certainmedicaltasks. In this study, we comparedbetweentwo different models: the Holt’s Winter(HW)model and the Linear Regression (LR) model.To obtain the data set of COVID-19, we accessed the website of the Malaysian Ministry of Health.From January 24th, 2020, through July 31st, 2021, daily confirmed instances were documented and saved in Microsoft Excel. Case forecasts for the next 14 days were generated in the Waikato Environment for Knowledge Analysis (WEKA), and the accuracy of the forecasting models was measured by means of the Mean Absolute Percentage Error (MAPE).According to the lowest value of performance indicators, the best model is picked. The results of the comparison demonstrate that Holt's Winter showed betterforecasting outcome than the Linear Regression model. The obtainedresultdepicted the forecasted model can be further analyzed for the purpose of COVID-19 preparation and control.

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利用线性回归和Holt冬季算法预测马来西亚新冠肺炎确诊病例

2019冠状病毒病大流行（新冠肺炎）已经出现，并正在全球迅速蔓延。因此，对普通人群进行新冠肺炎检测可能意义重大。在过去几年中，使用机器学习来抗击新冠肺炎的人数迅速增加，这是因为它能够快速扩大规模，具有更高的处理能力，而且它在某些医学领域比人们更值得信赖。在本研究中，我们比较了两种不同的模型：Holt's Winter（HW）模型和线性回归（LR）模型。为了获得新冠肺炎的数据集，我们访问了马来西亚卫生部的网站。从2020年1月24日到2021年7月31日，每天确诊的病例都被记录并保存在Microsoft Excel中。在怀卡托知识分析环境（WEKA）中生成了未来14天的案例预测，并通过平均绝对百分比误差（MAPE）来衡量预测模型的准确性。根据性能指标的最低值，选择最佳模型。比较结果表明，Holt的Winter模型比线性回归模型具有更好的预测效果。预测模型所获得的结果可以进一步分析，以用于新冠肺炎的准备和控制。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Integrated Engineering ENGINEERING, MULTIDISCIPLINARY-

CiteScore

1.40

自引率

0.00%

发文量

期刊介绍： The International Journal of Integrated Engineering (IJIE) is a single blind peer reviewed journal which publishes 3 times a year since 2009. The journal is dedicated to various issues focusing on 3 different fields which are:- Civil and Environmental Engineering. Original contributions for civil and environmental engineering related practices will be publishing under this category and as the nucleus of the journal contents. The journal publishes a wide range of research and application papers which describe laboratory and numerical investigations or report on full scale projects. Electrical and Electronic Engineering. It stands as a international medium for the publication of original papers concerned with the electrical and electronic engineering. The journal aims to present to the international community important results of work in this field, whether in the form of research, development, application or design. Mechanical, Materials and Manufacturing Engineering. It is a platform for the publication and dissemination of original work which contributes to the understanding of the main disciplines underpinning the mechanical, materials and manufacturing engineering. Original contributions giving insight into engineering practices related to mechanical, materials and manufacturing engineering form the core of the journal contents.