Tanujit Chakraborty

TL;DR: A hybrid approach based on autoregressive integrated moving average model and Wavelet-based forecasting model that can generate short-term forecasts of the number of daily confirmed cases for Canada, France, India, South Korea, and the UK and an optimal regression tree algorithm to find essential causal variables that significantly affect the case fatality rates for different countries are presented.

TL;DR: A hybrid approach based on autoregressive integrated moving average model and Wavelet-based forecasting model that can generate short-term forecasts of the number of daily confirmed cases for Canada, France, India, South Korea, and the UK and an optimal regression tree algorithm to find essential causal variables that significantly affect the case fatality rates for different countries are presented.

TL;DR: The results of this study indicate that dengue cases can be accurately forecasted over a sufficient time period using the proposed hybrid methodology.

TL;DR: In this article, the authors proposed an integrated approach based on linear and nonlinear models that can predict the unemployment rates more accurately, which guarantees that the proposed model cannot show "explosive" behavior or growing variance over time.

TL;DR: This article uses supervised learning techniques to model and select the optimal academic characteristics of students to enhance their placement probability and shows that the proposed hybrid CT–ANN model achieves greater accuracy in predicting students’ placement than conventional supervised learning models.