Intriguing of pharmaceutical product development processes with the help of artificial intelligence and deep/machine learning or artificial neural network
N Jariwala, CL Putta, K Gatade, M Umarji… - Journal of Drug Delivery …, 2023 - Elsevier
The objectives of current review are (1) to provide a historical overview of artificial
intelligence and deep/machine learning (AI & D/ML) or Artificial Neural Network (ANN)(2) to …
intelligence and deep/machine learning (AI & D/ML) or Artificial Neural Network (ANN)(2) to …
Implementation of hybrid neuro-fuzzy and self-turning predictive model for the prediction of concrete carbonation depth: A soft computing technique
Carbonation is one of the critical problems that affects the durability of reinforced concrete; it
is a reaction between CO 2 gas and Ca (OH) 2 when H 2 O is available, which forms …
is a reaction between CO 2 gas and Ca (OH) 2 when H 2 O is available, which forms …
Tuning OER electrocatalysts toward LOM pathway through the lens of multi-descriptor feature selection by artificial intelligence-based approach
From the thermodynamic and kinetic viewpoints, the oxygen evolution reaction (OER) is
central to the production of hydrogen through electrocatalytic water splitting process. As a …
central to the production of hydrogen through electrocatalytic water splitting process. As a …
Earth skin temperature long-term prediction using novel extended Kalman filter integrated with Artificial Intelligence models and information gain feature selection
Predictions of Earth skin temperature (EST) can provide essential information for diverse
engineering applications such as energy harvesting and agriculture activities. Several …
engineering applications such as energy harvesting and agriculture activities. Several …
Ensemble hybrid machine learning to simulate dye/divalent salt fractionation using a loose nanofiltration membrane
The escalating quantity of wastewater from multiple sources has raised concerns about both
water reuse and environmental preservation. Therefore, there is a pressing need for …
water reuse and environmental preservation. Therefore, there is a pressing need for …
[HTML][HTML] Emerging Harris Hawks Optimization based load demand forecasting and optimal sizing of stand-alone hybrid renewable energy systems–A case study of …
This paper presents load forecasting and optimal sizing for minimizing the Annualized Cost
of the System (ACS) of a stand-alone photovoltaic (PV)/wind/battery hybrid renewable …
of the System (ACS) of a stand-alone photovoltaic (PV)/wind/battery hybrid renewable …
Intelligent soft computational models integrated for the prediction of potentially toxic elements and groundwater quality indicators: a case study
JC Agbasi, JC Egbueri - Journal of sedimentary environments, 2023 - Springer
Reports have shown that potentially toxic elements (PTEs) in air, water, and soil systems
expose humans to carcinogenic and non-carcinogenic health risks. In southeastern Nigeria …
expose humans to carcinogenic and non-carcinogenic health risks. In southeastern Nigeria …
Interpretation the influence of hydrometeorological variables on soil temperature prediction using the potential of deep learning model
S Elsayed, M Gupta… - Knowledge …, 2023 - … journals.publicknowledgeproject.org
The importance of soil temperature (ST) quantification can contribute to diverse ecological
modelling processes as well as for agricultural activities. Over the literature, it was evident …
modelling processes as well as for agricultural activities. Over the literature, it was evident …
An overview of streamflow prediction using random forest algorithm
Since the first application of Artificial Intelligence in the field of hydrology, there has been a
great deal of interest in exploring aspects of future enhancements to hydrology. This is …
great deal of interest in exploring aspects of future enhancements to hydrology. This is …
[HTML][HTML] Multi-regional modeling of cumulative COVID-19 cases integrated with environmental forest knowledge estimation: A deep learning ensemble approach
Reliable modeling of novel commutative cases of COVID-19 (CCC) is essential for
determining hospitalization needs and providing the benchmark for health-related policies …
determining hospitalization needs and providing the benchmark for health-related policies …