Accurate specification of the drugs' solubility is known as an important activity to
appropriately manage the supercritical impregnation process. Over the last decades, the …

We developed two distinct regression models based on machine learning approach for
estimating CO 2 loading in solvents in this study. The methods of Adaptive boosted support …

The COVID-19 pandemic has pointed out the need for new technical approaches to
increase the preparedness of healthcare systems. One important measure is to develop …

With the increase adoption of monitoring technology for Smart Water Grid (SWG) system,
accurate prediction of SWG status is essential for water companies to effectively operate and …

This study evaluates the influence of water level fluctuations in a mountain reservoir on
potential changes in the morphology of its shore zone. The analysis was carried out in the …

In order to optimize productin of biodiesel from waste cooking oil utilizing Fe-exchanged
montmorillonite 12 K10 (Fe-MMT K10) heterogeneous catalyst was applied in this work. The …

Multivariate time series forecasting problem has attracted enormous research in recent
years, and many deep learning models have been proposed and claimed to be effective in …

Accurately predicting gas load is crucial for optimal planning and scheduling of natural gas
production. Existing machine learning or deep learning-based prediction methods primarily …

Nowadays, sustainable supplement of water has recently been identified as a vital necessity
due to the existence of limited drinkable water sources. To do this, various techniques are …

This work contributes to Short Term load forecasting methods by investigating the
performance of Prophet method and comparing it with that of Seasonality and Trend …