• Dr JULIE M DAVID
• NEENU
• Riya Azeez

The Novel Corona Virus 2019 is a respiratory problem that similar to pneumonia. It ‘s one of the most infectious diseases in the 21st century. This paper proposes the methodology is based on a hybrid model which combines the convolutional neural networks techniques and random forest model with extrapolations based on recurrent neural networks. This combination provides understandable results in relation of a coefficient that varies with the limitation measures, which may be further refined by expert rules that capture the expected changes in such measures. Random forest will help to reduces overfitting and helps to improve the accuracy. We propose an improved hybrid classification approach for COVID-19 images by combining the strengths of CNN to extract features to select the most relevant features. The suggested method was tested on two publicly available COVID-19 X-ray datasets, and it achieved great performance while reducing computing complexity.

Covid-19,Convolutional network, Random forest

"AN INTELLIGENT SYSTEM FOR THE PREDICTION OF COVID -19 ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.c267-c271, June-2022, Available :http://www.jetir.org/papers/JETIR2206233.pdf

"AN INTELLIGENT SYSTEM FOR THE PREDICTION OF COVID -19 ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. ppc267-c271, June-2022, Available at : http://www.jetir.org/papers/JETIR2206233.pdf