The spread of COVID-19 in the entire world has put human kind danger. assets probably biggest economies are worried because enormous infectivity and contagiousness this illness. ability ML models to conjecture quantity forthcoming patients influenced by which is considered as a likely danger humanity. Specifically, four standard estimating linear regression (LR), least total shrinkage determina...

Bridges are essential structures that connect riverbanks and facilitate transportation. However, bridge piers abutments can disrupt the natural flow of rivers, causing a rise in water levels upstream bridge. The levels, known as backwater or afflux, threaten stability service bridges riverbanks. It is postulated applications estimation models with more precise afflux predictions enhance safety ...

Abstract A new paradigm for data science has emerged, with quantum data, models, and computational devices. This field, called machine learning (QML), aims to achieve a speedup over traditional analysis. However, its success usually hinges on efficiently training the parameters in neural networks, field of QML is still lacking theoretical scaling results their trainability. Some trainability ha...

The complexity and dynamics of catalytic systems make it challenging to study the catalysts reactions. Fortunately, advance machine learning (ML) has made descriptor-based catalyst screening rational design a mainstream research approach. Herein, spectroscopic descriptors reported in recent years are highlighted field catalysis. Both vibrational spectra X-ray absorption have demonstrated strong...

The hydraulic conductivity of saturated soil is a crucial parameter in the study any engineering problem concerning groundwater. Hydraulic mainly depends on particle size distribution, compaction, and properties that influence aggregation water retention. Generally, finding simple accurate analytical equations between characteristics which it very hard task. Machine learning algorithms can prov...