Data based Analysis, Modeling and Forecasting of Novel Coronavirus in infected regions using Extreme Learning Machine algorithm

Abstract

In current development in science and technology, Machine learning algorithms play an essential role for prediction, classification, data analysis and data visualization. With this efficient algorithm, we can solve many real-world problems in all domains like education, healthcare, banking, geographical analysis, etc., in the current scenario; much research work is going on with the new virus's infection called the corona. This Corona virus is a comprehensive unit of virus this cause illness in humans or animals, now in East Asian countries, this virus affected more people. In India, the first case was found in January month, originated from China. The entire world is focusing on the disease, and day by day, the infection and death rate is increasing. In this, we intended to focus on the spread of this deadly disease and to demonstrate which countries are the most affected by doing statistical analysis. On December 2019, As of 10 February 2020, China reported overall of 40,235 cases 909 deaths, evoking local and foreign terror. Here we provide estimates of the major epidemiological parameters, Based on the epidemiological data available to the public for Hubei, China, 11 January to 10 February 2020. In particular, we give an estimate Fatality and case recovery rates, along with their 90 per cent confidence levels as the epidemic progresses. For this work implementation, Extreme Learning Machine algorithm used. ELM is a feed-forward network and its learning rate also fast when compare to normal neural network. No need to provide any weights and bias values. This algorithm will give a promising result with the best accuracy.