[HTML][HTML] A review of physics-based machine learning in civil engineering
The recent development of machine learning (ML) and Deep Learning (DL) increases the
opportunities in all the sectors. ML is a significant tool that can be applied across many …
opportunities in all the sectors. ML is a significant tool that can be applied across many …
Artificial intelligence algorithms for prediction and sensitivity analysis of mechanical properties of recycled aggregate concrete: A review
Using recycled aggregates generated from demolition waste for concrete production is a
promissory option to reduce the environmental footprint of the built environment. However …
promissory option to reduce the environmental footprint of the built environment. However …
Compressive strength prediction of basalt fiber reinforced concrete via random forest algorithm
H Li, J Lin, X Lei, T Wei - Materials Today Communications, 2022 - Elsevier
Basalt fiber is a green non-polluting material with strong tensile mechanical properties. In
this paper, the strength prediction model of basalt fiber concrete is constructed by random …
this paper, the strength prediction model of basalt fiber concrete is constructed by random …
Modeling strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface
This study investigated the importance of applying explainable artificial intelligence (XAI) on
different machine learning (ML) models developed to predict the strength characteristics of …
different machine learning (ML) models developed to predict the strength characteristics of …
Fractionation of dyes/salts using loose nanofiltration membranes: Insight from machine learning prediction
Wastewater (WW) served as the crucial indicator for sustainable development, human
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …
[HTML][HTML] A systematic review on automated human emotion recognition using electroencephalogram signals and artificial intelligence
Abstract Brain-Computer Interaction (BCI) system intelligence has become more dependent
on electroencephalogram (EEG)-based emotion recognition because of the numerous …
on electroencephalogram (EEG)-based emotion recognition because of the numerous …
New generation neurocomputing learning coupled with a hybrid neuro-fuzzy model for quantifying water quality index variable: A case study from Saudi Arabia
Ensuring availability in terms of quality and quantity and sustainable management of safe,
affordable drinking water is one of the integral parts of envisioning the 2030 Sustainable …
affordable drinking water is one of the integral parts of envisioning the 2030 Sustainable …
Towards sustainable construction: machine learning based predictive models for strength and durability characteristics of blended cement concrete
Supplementary cementitious materials (SCMs) are widely utilized in concrete mixtures,
either substituting a part of the cement content or replacing a portion of clinker in cement …
either substituting a part of the cement content or replacing a portion of clinker in cement …
[HTML][HTML] Evaluation of gene expression programming and artificial neural networks in PyTorch for the prediction of local scour depth around a bridge pier
WH Hassan, HH Hussein, MH Alshammari… - Results in …, 2022 - Elsevier
Local scouring around the piers of bridges has been identified as one of the main problems
contributing to bridge failure globally. As such, the accurate prediction of safe scouring …
contributing to bridge failure globally. As such, the accurate prediction of safe scouring …
Prediction and uncertainty quantification of ultimate bond strength between UHPC and reinforcing steel bar using a hybrid machine learning approach
The composite action of the reinforcing bars in the UHPC involves complex and nonlinear
mechanisms. Inadequate knowledge of their interaction may lead to insufficient bond …
mechanisms. Inadequate knowledge of their interaction may lead to insufficient bond …