In this world, several types of soils are available with their different engineering properties.
Determining each soil's engineering properties is difficult because the laboratory procedures …

In this study, gene expression programming (GEP) and multi gene expression programming
(MEP) are utilized to formulate new prediction models for determining the compaction …

Machine Learning for Materials Science is a primer on the subject that also delves into the
specifics of where ML might be applied to materials science research. With a focus on where …

This work introduces an optimal performance model for predicting the unconfined
compressive strength (UCS) of lime-stabilized soil using the machine (ensemble tree (ET) …

An accurate evaluation of the clay's properties when mixed with recyclable materials is the
end objective of many geotechnical experimental efforts. However, experimental studies …

The present research introduces the best architecture model for predicting the unsoaked
California bearing ratio (CBRu) of soil by comparing the models based on the least square …

The effective way of recycling waste polyethylene terephthalate (PET) by exposing it to
gamma rays, is adopted in formulating the compositions of cementitious grouts for semi …

The present research employs the models based on the relevance vector machine (RVM)
approach to predict the unconfined compressive strength (UCS) of the cohesive virgin (fine …

Glass fiber reinforced polymer (GFRP) rebars reinforced in concrete are susceptible to
degradation in harsh alkaline environments such as moist reinforced concrete and seawater …

Plastic electronic waste (E-waste) is constantly growing around the world owing to the rapid
increase in industrialization, urbanization, and population. The current annual production …