Predicting the compaction characteristics of expansive soils using two genetic programming-based algorithms
In this study, gene expression programming (GEP) and multi gene expression programming
(MEP) are utilized to formulate new prediction models for determining the compaction …
(MEP) are utilized to formulate new prediction models for determining the compaction …
New prediction models for the compressive strength and dry-thermal conductivity of bio-composites using novel machine learning algorithms
Bio-composites have become the prime material selection for green concrete because of the
increasing awareness of environmental issues. Due to their highly heterogenous nature …
increasing awareness of environmental issues. Due to their highly heterogenous nature …
[HTML][HTML] Optimizing durability assessment: Machine learning models for depth of wear of environmentally-friendly concrete
The use of fly ash in cementitious composites has gained popularity. However, assessing
the depth of wear (DW) of concrete requires expensive and destructive laboratory tests …
the depth of wear (DW) of concrete requires expensive and destructive laboratory tests …
[HTML][HTML] Machine learning based computational approach for crack width detection of self-healing concrete
Concrete structures frequently experience the phenomena of crack development. The
researchers used certain healing agents to boost the frequently observed autogenous crack …
researchers used certain healing agents to boost the frequently observed autogenous crack …
[HTML][HTML] A data-driven approach to predict the compressive strength of alkali-activated materials and correlation of influencing parameters using SHapley Additive …
This research used gene expression programming (GEP) and multi expression
programming (MEP) to determine the compressive strength (CS) of alkali-activated material …
programming (MEP) to determine the compressive strength (CS) of alkali-activated material …
[HTML][HTML] Prediction of sustainable concrete utilizing rice husk ash (RHA) as supplementary cementitious material (SCM): Optimization and hyper-tuning
Rice Husk ash (RHA) utilization in concrete as a waste material can contribute to the
formation of a robust cementitious matrix with utmost properties. The strength of HPC when …
formation of a robust cementitious matrix with utmost properties. The strength of HPC when …
Prediction of building energy performance using mathematical gene-expression programming for a selected region of dry-summer climate
Developing energy-efficient buildings considering building design parameters can help
reduce buildings' energy consumption. The energy efficiency of residential buildings is …
reduce buildings' energy consumption. The energy efficiency of residential buildings is …
[HTML][HTML] Optimizing compressive strength prediction models for rice husk ash concrete with evolutionary machine intelligence techniques
This research intended to increase the understanding of using modern machine intelligence
techniques, including multi-expression programming (MEP) and gene expression …
techniques, including multi-expression programming (MEP) and gene expression …
[HTML][HTML] Evaluation of properties of bio-composite with interpretable machine learning approaches: optimization and hyper tuning
Hemp bio-composite (HBC) is a sustainable material that can be considered as a “carbon
negative” or “better-than-zero-carbon” because it absorbs more carbon from its surrounding …
negative” or “better-than-zero-carbon” because it absorbs more carbon from its surrounding …
The influence of cost of debt, cost of equity and weighted average cost of capital on dividend policy decision: Evidence from non-financial companies listed on the …
R Arhinful, L Mensah, HIM Amin, HA Obeng - Future Business Journal, 2024 - Springer
Non-financial companies listed on the Frankfurt Stock Exchange face considerable
difficulties due to expensive funding and the need to make complex decisions about their …
difficulties due to expensive funding and the need to make complex decisions about their …