Classification and Categorization of COVID-19 Outbreak in Pakistan
Classification and Categorization of COVID-19 Outbreak in Pakistan
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DOI：
10.32604/cmc.2021.015655
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发表时间：
2021-01-01
影响因子：
3.1
通讯作者：
Alkahtani, Mohammed
中科院分区：
文献类型：
--
作者：
Ayoub, Amber;Mahboob, Kainaat;Alkahtani, Mohammed
冠状病毒是一种潜在的致命疾病，通常发生在哺乳动物和鸟类身上。一般来说，在人类中，病毒通过从感染者体内分泌的任何类型的液体的飞沫传播。冠状病毒是一种比其他无预谋病毒更致命的病毒家族。2019年12月，中国武汉市出现了新型冠状病毒（COVID-19）。自2020年1月23日以来，感染人数迅速增加，影响到包括巴基斯坦在内的许多国家的卫生和经济。本研究的目的是提供一个系统，根据每天从巴基斯坦不同地区收集的数据，对巴基斯坦的COVID-19疫情进行分类和分类。本研究还比较了机器学习分类器（即决策树（DT）、朴素贝叶斯（NB）、支持向量机和逻辑回归）在巴基斯坦收集的COVID-19数据集上的性能。实验结果表明，DT和NB分类器的分类性能优于其他分类器。此外，通过实现贝叶斯正则化人工神经网络（BRANN）分类器对分类数据进行分类。结果表明，BRANN分类器优于最先进的分类器。
Coronavirus is a potentially fatal disease that normally occurs in mammals and birds. Generally, in humans, the virus spreads through aerial droplets of any type of fluid secreted from the body of an infected person. Coronavirus is a family of viruses that is more lethal than other unpremeditated viruses. In December 2019, a new variant, i.e., a novel coronavirus (COVID-19) developed in Wuhan province, China. Since January 23, 2020, the number of infected individuals has increased rapidly, affecting the health and economies of many countries, including Pakistan. The objective of this research is to provide a system to classify and categorize the COVID-19 outbreak in Pakistan based on the data collected every day from different regions of Pakistan. This research also compares the performance of machine learning classifiers (i.e., Decision Tree (DT), Naive Bayes (NB), Support Vector Machine, and Logistic Regression) on the COVID-19 dataset collected in Pakistan. According to the experimental results, DT and NB classifiers outperformed the other classifiers. In addition, the classified data is categorized by implementing a Bayesian Regularization Artificial Neural Network (BRANN) classifier. The results demonstrate that the BRANN classifier outperforms state-of-the-art classifiers.