Water quality has a significant influence on human health. As a result, water quality
parameter modelling is one of the most challenging problems in the water sector. Therefore …

Reservoir water level (RWL) prediction has become a challenging task due to spatio-
temporal changes in climatic conditions and complicated physical process. The Red Hills …

Hybrid models such as the Artificial Neural Network-Autoregressive Integrated Moving
Average (ANN–ARIMA) model are widely used in forecasting. However, inaccuracies and …

Improving forecasting particularly time series forecasting accuracy, efficiency and precisely
become crucial for the authorities to forecast, monitor, and prevent the COVID-19 cases so …

Forecasting is a very effortful task owing to its features which simultaneously contain linear
and nonlinear patterns. The Autoregressive Integrated Moving Average (ARIMA) model has …

Improving forecasts, particularly the accuracy, efficiency, and precision of time-series
forecasts, is becoming critical for authorities to predict, monitor, and prevent the spread of …

ABSTRACT The Mekong Delta is the most severely affected area by saltwater intrusion in
Vietnam. Recent studies have focused on predicting this disaster with weekly and decade …

With the gradual integration of global economy and finance, the financial market presents
many complex financial phenomena. To increase the prediction accuracy of financial data, a …

The Logistic Regression Model (LRM) is successful in many fields due to its capability of
predicting and describing the relationship between binary response variables and one or …

Overpopulation, industrialization, urbanization, and the spreading out of irrigated agricultural
lands are the driving forces to increase the demand of water in the Kingdom of Saudi Arabia …