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 …
Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend
R Kazemi - Engineering Reports, 2023 - Wiley Online Library
Advanced concrete technology is the science of efficient, cost‐effective, and safe design in
civil engineering projects. Engineers and concrete designers are generally faced with the …
civil engineering projects. Engineers and concrete designers are generally faced with the …
Interpretable machine learning for predicting the strength of 3D printed fiber-reinforced concrete (3DP-FRC)
This study aims to provide an effective and accurate machine learning approach to predict
the compressive strength (CS) and flexural strength (FS) of 3D printed fiber reinforced …
the compressive strength (CS) and flexural strength (FS) of 3D printed fiber reinforced …
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 …
[HTML][HTML] Compressive strength prediction of rice husk ash using multiphysics genetic expression programming
Rice husk ash (RHA) is obtained by burning rice husks. An advanced programming
technique known as genetic expression programming (GEP) is used in this research for …
technique known as genetic expression programming (GEP) is used in this research for …
Flexural and split tensile strength of concrete with basalt fiber: An experimental and computational analysis
F Almohammed, MS Thakur, D Lee, R Kumar… - … and Building Materials, 2024 - Elsevier
The objective of this study is to create comprehensive multiscale models for predicting the
split tensile strength (STS) and flexural strength (FS) of basalt fiber-reinforced concrete, with …
split tensile strength (STS) and flexural strength (FS) of basalt fiber-reinforced concrete, with …
Machine learning models for biomass energy content prediction: a correlation-based optimal feature selection approach
In this study, a multilinear regression (MLR) and three machine learning techniques, ie, an
adaptive neuro-fuzzy inference system (ANFIS), an artificial neural network (ANN), and a …
adaptive neuro-fuzzy inference system (ANFIS), an artificial neural network (ANN), and a …
Earth skin temperature long-term prediction using novel extended Kalman filter integrated with Artificial Intelligence models and information gain feature selection
Predictions of Earth skin temperature (EST) can provide essential information for diverse
engineering applications such as energy harvesting and agriculture activities. Several …
engineering applications such as energy harvesting and agriculture activities. Several …
[HTML][HTML] Emerging Harris Hawks Optimization based load demand forecasting and optimal sizing of stand-alone hybrid renewable energy systems–A case study of …
This paper presents load forecasting and optimal sizing for minimizing the Annualized Cost
of the System (ACS) of a stand-alone photovoltaic (PV)/wind/battery hybrid renewable …
of the System (ACS) of a stand-alone photovoltaic (PV)/wind/battery hybrid renewable …
An overview of streamflow prediction using random forest algorithm
Since the first application of Artificial Intelligence in the field of hydrology, there has been a
great deal of interest in exploring aspects of future enhancements to hydrology. This is …
great deal of interest in exploring aspects of future enhancements to hydrology. This is …