P. Prabhu¹, P. Valarmathie^2,*, K. Dinakaran³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2989-3005, 2023, DOI:10.32604/iasc.2023.028659 - 15 March 2023

Abstract Supportive learning plays a substantial role in providing a quality education system. The evaluation of students’ performance impacts their deeper insight into the subject knowledge. Specifically, it is essential to maintain the baseline foundation for building a broader understanding of their careers. This research concentrates on establishing the students’ knowledge relationship even in reduced samples. Here, Synthetic Minority Oversampling TEchnique (SMOTE) technique is used for pre-processing the missing value in the provided input dataset to enhance the prediction accuracy. When the initial processing is not done substantially, it leads to misleading prediction accuracy. This research… More >

Meshrif Alruily¹, Mohamed Ezz^1,2, Ayman Mohamed Mostafa^1,3, Nacim Yanes^1,4, Mostafa Abbas⁵, Yasser El-Manzalawy^5,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1751-1768, 2022, DOI:10.32604/cmc.2022.020714 - 03 November 2021

Abstract Accurate forecasting of emerging infectious diseases can guide public health officials in making appropriate decisions related to the allocation of public health resources. Due to the exponential spread of the COVID-19 infection worldwide, several computational models for forecasting the transmission and mortality rates of COVID-19 have been proposed in the literature. To accelerate scientific and public health insights into the spread and impact of COVID-19, Google released the Google COVID-19 search trends symptoms open-access dataset. Our objective is to develop 7 and 14-day-ahead forecasting models of COVID-19 transmission and mortality in the US using the… More >