COVID-19 is a new member of the Coronaviridae family that has serious effects on respiratory, gastrointestinal, and neurological systems. COVID-19 spreads quickly worldwide and affects more than 41.5 million persons (till 23 October 2020). It has a high hazard to the safety and health of people all over the world. COVID-19 has been declared as a global pandemic by the World Health Organization (WHO). Therefore, strict special policies and plans should be made to face this pandemic. Forecasting COVID-19 cases in hotspot regions is a critical issue, as it helps the policymakers to develop their future plans. In this paper, we propose a new short term forecasting model using an enhanced version of the Adaptive Neuro-Fuzzy Inference System (ANFIS). An improved Marine Predators Algorithm (MPA), called Chaotic MPA (CMPA), is applied to enhance the ANFIS and to avoid its shortcomings. More so, we compared the proposed CMPA with three artificial intelligence-based models include the original ANFIS, and two modified versions of ANFIS model using both of the original Marine Predators Algorithm (MPA) and Particle Swarm Optimization (PSO). The forecasting accuracy of the models was compared using different statistical assessment criteria. CMPA significantly outperformed all other investigated models.

中文翻译：

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俄罗斯和巴西 COVID-19 爆发的高效人工智能预测模型

COVID-19 是冠状病毒科的新成员，对呼吸系统、胃肠道和神经系统有严重影响。COVID-19 在全球迅速传播，影响超过 4150 万人（截至 2020 年 10 月 23 日）。它对全世界人民的安全和健康都具有很高的危害。COVID-19 已被世界卫生组织 (WHO) 宣布为全球大流行病。因此，应对这一流行病，应制定严格的特殊政策和计划。预测热点地区的 COVID-19 病例是一个关键问题，因为它有助于政策制定者制定未来计划。在本文中，我们使用自适应神经模糊推理系统（ANFIS）的增强版本提出了一种新的短期预测模型。一种改进的海洋捕食者算法 (MPA)，称为混沌 MPA (CMPA)，用于增强 ANFIS 并避免其缺点。更重要的是，我们将提议的 CMPA 与三个基于人工智能的模型进行了比较，包括原始 ANFIS，以及两个使用原始海洋捕食者算法 (MPA) 和粒子群优化 (PSO) 的 ANFIS 模型的修改版本。使用不同的统计评估标准比较模型的预测准确性。CMPA 显着优于所有其他研究模型。使用不同的统计评估标准比较模型的预测准确性。CMPA 显着优于所有其他研究模型。使用不同的统计评估标准比较模型的预测准确性。CMPA 显着优于所有其他研究模型。