Covid-19 Forecasting using Supervised Machine Learning Techniques – Survey

COVID-19 is a global epidemic that has spread to over 170 nations. In practically all of the countries affected, the number of infected and death cases has been rising rapidly. Forecasting approaches can be implemented, resulting in the development of more effective strategies and the making of more informed judgments. These strategies examine historical data in order to make more accurate predictions about what will happen in the future. These forecasts could aid in preparing for potential risks and consequences. In order to create accurate findings, forecasting techniques are crucial. Forecasting strategies based on Big data analytics acquired from National databases (or) World Health Organization, as well as machine learning (or) data science techniques are classified in this study. This study shows the ability to predict the number of cases affected by COVID-19 as potential risk to mankind

A study on Rainfall-Runoff Relationship using NRCS-CN and Remote Sensing Technology in Deh Sabz sub basin,

Abstract—Rainfall-runoff relationship is one of the most important phenomena in hydrology design of hydrological structures and drainage systems. Estimation of the runoff is required in order to determine and forecast its effects. Excessive runoff can cause floods with danger to life and property. Excessive runoff can washout the surface soil and because of this agricultural cycle of an area can be damaged forever. In a smaller scale, excessive runoff can disrupt life in residential areas and agriculture in rural areas. The runoff curve number (CN) is a key factor in determining runoff in the NCRS (National Resource Conservation Service) based hydrologic modeling method. The traditional NRCS-CN method for calculating the composite curve number is very tedious and consumes a major portion of the hydrologic modeling time. Therefore, geographi

Estimation Of Confined Aquifer Parameters Of Polecharkhi Sub-basin Of Kabul Basin

Abstract—Evaluation of confined aquifer parameters, namely, transmissivity T, storage coefficient S and hydrological boundaries, from pump-test data has been a continual field of research.A simple method by Sushil K. Singh has been presented for precise determination of aquifer parameters using early drawdown data. The principle objective of this study is to estimate the confined aquifer parameters of the Polecharkhi sub-basin of Kabul basin as accurate, reliable and economical as possible. Also to determine the parameters, hydrological boundaries and their respond to pumping with a method with site applicability. And also to determine the parameters with short time of pump test and early drawdown data or abandoned pump test data with a method applicable to time and resource constraints. The first study to estimate the aquifer parameters from pump test was analytically derived by Theis (1935), which is valid for groundwater radial unsteady flow based on the Darcy law. Using the present method the confined aquifer parameters of Pol-e-Charkhy sub-basin is estimated in only one point. In general the transmissivity of confined aquifer of Polecharkhi sub-basin is 96.03m^2/day and the storage coefficient is 0.00234. The reliability of these values is judged by calculation of the Standard Error of Estimate (SEE) considering variations of observed and computed drawdown for early as well as late drawdown data. The value of SEE = 7.7 * 10^-4 and the This value shows the reliability of this method compared to other existing methods in the literature while this method used early drawdown data and again reproduced the early and late time drawdown data using estimated aquifer parameters(T&S) with such a SEE value. As the confined aquifer of Kabul basin is like fossil there is no leakage between confined and unconfined is reported and also there is no recharge boundary is available [JICA]