Investigating Epidemic Growth of COVID-19 in Saudi Arabia based on Time Series Models

Faculty Computer Science Year: 2020
Type of Publication: ZU Hosted Pages: 459 - 466
Authors:
Journal: International Journal of Advanced Computer Science and Applications Science and Information Organization Volume: 11
Keywords : Investigating Epidemic Growth , COVID-19 , Saudi Arabia    
Abstract:
Predictive mathematical models for simulating the spread of the COVID-19 pandemic are an interesting and fundamental approach to understand the infection growth curve of the epidemic and to plan effective control strategies. Time series pre
   
     
 
       

Author Related Publications

  • Wael Said AbdelMageed Mohamed, "A big data approach to sentiment analysis using greedy feature selection with cat swarm optimization-based long short-term memory neural networks", Springer Nature, 2018 More
  • Wael Said AbdelMageed Mohamed, "High-Precision Brain Tumor Diagnosis Using SECNN-MNet Framework and Explainable AI", Springer Nature Link, 2025 More
  • Wael Said AbdelMageed Mohamed, "Deception and cloud integration: A multi-layered approach for DDoS detection, mitigation, and attack surface minimization in SD-IoT networks", .Elsevier Ltd, 2025 More
  • Wael Said AbdelMageed Mohamed, "Reinforcement Learning for Industrial Automation: A Comprehensive Review of Adaptive Control and Decision-Making in Smart Factories", MDPI, 2025 More
  • Wael Said AbdelMageed Mohamed, "RAUM-GANs: A Multi-Layer GAN-Enhanced Framework for Accurate Multiple Sclerosis Lesion Segmentation in MRI", Nature Portfolio, 2025 More

Department Related Publications

  • Ibrahiem Mahmoud Mohamed Elhenawy, "BERT-CNN: A Deep Learning Model for Detecting Emotions from Text", Tech Science Press, 2021 More
  • Ahmed Raafat Abass Mohamed Saliem, "BERT-CNN: A Deep Learning Model for Detecting Emotions from Text", Tech Science Press, 2021 More
  • Ahmed Raafat Abass Mohamed Saliem, "Using General Regression with Local Tuning for Learning Mixture Models from Incomplete Data Sets", ScienceDirect, 2010 More
  • Ahmed Raafat Abass Mohamed Saliem, "On determining efficient finite mixture models with compact and essential components for clustering data", ScienceDirect, 2013 More
  • Ahmed Raafat Abass Mohamed Saliem, "Unsupervised learning of mixture models based on swarm intelligence and neural networks with optimal completion using incomplete data", ScienceDirect, 2012 More
Tweet