Machine learning in environmental research: common pitfalls and best practices
Machine learning (ML) is increasingly used in environmental research to process large data
sets and decipher complex relationships between system variables. However, due to the …
sets and decipher complex relationships between system variables. However, due to the …
Machine learning for structural engineering: A state-of-the-art review
HT Thai - Structures, 2022 - Elsevier
Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …
intelligence (AI). It provides a unique opportunity to make structural engineering more …
Predictive models for concrete properties using machine learning and deep learning approaches: A review
Concrete is one of the most widely used materials in various civil engineering applications.
Its global production rate is increasing to meet demand. Mechanical properties of concrete …
Its global production rate is increasing to meet demand. Mechanical properties of concrete …
Innovative modeling techniques including MEP, ANN and FQ to forecast the compressive strength of geopolymer concrete modified with nanoparticles
The use of nano-materials to improve the engineering properties of different types of
concrete composites including geopolymer concrete (GPC) has recently gained popularity …
concrete composites including geopolymer concrete (GPC) has recently gained popularity …
RETRACTED: Fresh and mechanical performances of recycled plastic aggregate geopolymer concrete modified with Nano-silica: Experimental and computational …
HU Ahmed, AS Mohammed, AA Mohammed - 2023 - Elsevier
Following receipt of a reader complaint, it was established that this paper [https://doi.
org/10.1016/j. conbuildmat. 2023.132266] and another submitted to the Journal of Building …
org/10.1016/j. conbuildmat. 2023.132266] and another submitted to the Journal of Building …
Support vector regression (SVR) and grey wolf optimization (GWO) to predict the compressive strength of GGBFS-based geopolymer concrete
Geopolymer concrete is an eco-efficient and environmentally friendly construction material.
Various ashes were used as the binder in geopolymer concrete, such as fly ash, ground …
Various ashes were used as the binder in geopolymer concrete, such as fly ash, ground …
Compressive strength of geopolymer concrete composites: a systematic comprehensive review, analysis and modeling
The desire to make the concrete industry more environmentally friendly has existed for a
long time. Geopolymer concrete, which uses industrial or agricultural by-product ashes as …
long time. Geopolymer concrete, which uses industrial or agricultural by-product ashes as …
Predicting the compressive strength of normal and High-Performance Concretes using ANN and ANFIS hybridized with Grey Wolf Optimizer
Achieving a reliable model for predicting the compressive strength (CS) of concrete can
save in time, energy, and cost and also provide information about scheduling for …
save in time, energy, and cost and also provide information about scheduling for …
Prediction of mechanical properties of green concrete incorporating waste foundry sand based on gene expression programming
Waste foundry sand (WFS) is a major pollutant generated from metal casting foundries and
is classified as a hazardous material due to the presence of organic and inorganic pollutants …
is classified as a hazardous material due to the presence of organic and inorganic pollutants …
Soft computing models to predict the compressive strength of GGBS/FA-geopolymer concrete
A variety of ashes used as the binder in geopolymer concrete such as fly ash (FA), ground
granulated blast furnace slag (GGBS), rice husk ash (RHA), metakaolin (MK), palm oil fuel …
granulated blast furnace slag (GGBS), rice husk ash (RHA), metakaolin (MK), palm oil fuel …