Ram Kumar Singh

TL;DR: A comparison was done between the identified top 15 countries for confirmed cases, deaths, and recoveries, and an advanced autoregressive integrated moving average (ARIMA) model was used for predicting the COVID-19 disease spread trajectories for the next 2 months.

TL;DR: This study test the application of the multilayer perceptron neural network (MLP-NN) to project the future Agriculture, Forestry and Other Land Use (AFOLU) for the year 2050 for the South Asian Association for Regional Cooperation (SAARC) nations to assist planners and policymakers to develop nations’ specific strategy to proportionate land use classes to meet various needs on a sustainable basis.

TL;DR: In this paper, the vulnerability of forests in the Indian Western Himalayan (IWH) region comprising the states of Jammu & Kashmir (J&K), Himachal Pradesh (HP) and Uttarakhand (UK) was done using six indicators of vulnerability in the form of biological richness index, disturbance index, forest canopy density, fire point intensity and forest extraction intensity of fringe forests.

TL;DR: The comparison between identified top-15 countries for confirmed, death and recovery of the cases and further advanced Auto-Regressive Integrated Moving Average Model (ARIMA) for predicting the spreading of COVID-19 disease trajectories for next two months are compared.

TL;DR: This study predicted some trajectories of trajectories associated with COVID-19 in the coming days in India using an Auto-regression integrated moving average model (ARIMA) and Richards model to strengthen the implementation of strategies to increase the health system capacity and enactment of social distancing measures all over India.