Time series data are data which are taken in a particular time interval, and may vary
drastically during the period of observation and hence it becomes highly nonlinear. Stock …

Over the past decades, the major objectives of computer design have been to improve
performance and to reduce cost, energy consumption, and size, while security has remained …

Stock market is a significant element of economic market. Accurate forecasting of stock
market is very helpful to shareholders because future prediction of a stock value will elevate …

The water level in the reservoir is an important factor in the operation of a hydroelectric
turbine to control water overflow so that there is no excessive degradation. This water control …

This paper explores and compares regression technique with ensemble regression
techniques in view of two ensemble learning: Bagging and Boosting (Least Square Boost …

Forecasting about the Novel coronavirus disease 2019 (COVID-19) pandemic involves high
uncertainty and may be affected by measures taken by the government to fight the disease …

The precise forecasting of stock prices is not possible because of the complexity and
uncertainty of stock. The effectual model is needed for the triumphant assessment of …

Stock market prediction is a very tough task in the finance world. Since stock prices are
dynamic, noisy, non-scalable, non-linear, non-parametric and complicated. In recent years …

In recent years climate prediction has obtained more attention to mitigate the impact of
natural disasters caused by climatic variability. Efficient and effective climate prediction …

Forecasting stock market movements is a challenging and significant task for both
researchers and investors. Stock market movements are affected by local and global …