Influence of data splitting on performance of machine learning models in prediction of shear strength of soil
The main objective of this study is to evaluate and compare the performance of different
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
Revealing the nature of metakaolin-based concrete materials using artificial intelligence techniques
In this study, a model for the estimation of the compressive strength of concretes
incorporating metakaolin is developed and parametrically evaluated, using soft computing …
incorporating metakaolin is developed and parametrically evaluated, using soft computing …
Introducing stacking machine learning approaches for the prediction of rock deformation
Accurate and reliable predictions of rock deformations are crucial in many rock-based
projects in civil and mining engineering. In this research, a new system for the prediction of …
projects in civil and mining engineering. In this research, a new system for the prediction of …
Prediction of cement-based mortars compressive strength using machine learning techniques
The application of artificial neural networks in mapping the mechanical characteristics of the
cement-based materials is underlined in previous investigations. However, this machine …
cement-based materials is underlined in previous investigations. However, this machine …
[HTML][HTML] A novel feature selection approach based on tree models for evaluating the punching shear capacity of steel fiber-reinforced concrete flat slabs
When designing flat slabs made of steel fiber-reinforced concrete (SFRC), it is very important
to predict their punching shear capacity accurately. The use of machine learning seems to …
to predict their punching shear capacity accurately. The use of machine learning seems to …
A new auto-tuning model for predicting the rock fragmentation: a cat swarm optimization algorithm
J Huang, PG Asteris, S Manafi Khajeh Pasha… - Engineering with …, 2022 - Springer
The main focus of the present work is to offer an auto-tuning model, called cat swarm
optimization (CSO), to predict rock fragmentation. This population-based method has a …
optimization (CSO), to predict rock fragmentation. This population-based method has a …
Predicting the thermal conductivity of soils using integrated approach of ANN and PSO with adaptive and time-varying acceleration coefficients
This study aims to propose hybrid adaptive neuro swarm intelligence (HANSI) techniques for
predicting the thermal conductivity of unsaturated soils. The novel contribution is made by …
predicting the thermal conductivity of unsaturated soils. The novel contribution is made by …
Proposing several hybrid PSO-extreme learning machine techniques to predict TBM performance
A proper planning schedule for tunnel boring machine (TBM) construction is considered as a
necessary and difficult task in tunneling projects. Therefore, prediction of TBM performance …
necessary and difficult task in tunneling projects. Therefore, prediction of TBM performance …
An efficient optimal neural network based on gravitational search algorithm in predicting the deformation of geogrid-reinforced soil structures
The deformation of a Geosynthetic reinforced soil (GRS) structure is a key factor in designing
this type of retaining structures. On the other hand, the feasibility of artificial intelligence …
this type of retaining structures. On the other hand, the feasibility of artificial intelligence …
Prediction of air-overpressure induced by blasting using an ANFIS-PNN model optimized by GA
H Harandizadeh, DJ Armaghani - Applied Soft Computing, 2021 - Elsevier
Blasting operations typically have several negative impacts upon human beings and
constructions in adjacent region. Among all, air-overpressure (AOp) has been persistently …
constructions in adjacent region. Among all, air-overpressure (AOp) has been persistently …