Stop oversampling for class imbalance learning: A review

AS Tarawneh, AB Hassanat, GA Altarawneh… - IEEE …, 2022 - ieeexplore.ieee.org
For the last two decades, oversampling has been employed to overcome the challenge of
learning from imbalanced datasets. Many approaches to solving this challenge have been …

Rdpvr: Random data partitioning with voting rule for machine learning from class-imbalanced datasets

AB Hassanat, AS Tarawneh, SS Abed, GA Altarawneh… - Electronics, 2022 - mdpi.com
Since most classifiers are biased toward the dominant class, class imbalance is a
challenging problem in machine learning. The most popular approaches to solving this …

Predicting the geopolymerization process of fly ash-based geopolymer using deep long short-term memory and machine learning

H Tanyildizi - Cement and Concrete Composites, 2021 - Elsevier
In this study, the geopolymerization process of fly ash-based geopolymer was estimated
using the deep long short-term memory (LSTM) and machine learning models. The k …

Deepknuckle: Deep learning for finger knuckle print recognition

AS Tarawneh, AB Hassanat, E Alkafaween, B Sarayrah… - Electronics, 2022 - mdpi.com
Biometric technology has received a lot of attention in recent years. One of the most
prevalent biometric traits is the finger-knuckle print (FKP). Because the dorsal region of the …

Stock price forecasting for jordan insurance companies amid the covid-19 pandemic utilizing off-the-shelf technical analysis methods

GA Altarawneh, AB Hassanat, AS Tarawneh… - Economies, 2022 - mdpi.com
One of the most difficult problems analysts and decision-makers may face is how to improve
the forecasting and predicting of financial time series. However, several efforts were made to …

Prediction of compressive strength of nano-silica modified engineering cementitious composites exposed to high temperatures using hybrid deep learning models

H Tanyildizi - Expert Systems with Applications, 2024 - Elsevier
This study estimated the compressive strength of nano-silica-modified engineering
cementitious composites subjected to high temperatures using innovative hybrid deep …

Feature importance of stabilised rammed earth components affecting the compressive strength calculated with explainable artificial intelligence tools

H Anysz, Ł Brzozowski, W Kretowicz, P Narloch - Materials, 2020 - mdpi.com
Cement-stabilized rammed earth (CSRE) is a sustainable construction material. The use of it
allows for economizing on the cost of a structure. These two properties of CSRE are based …

Artificial neural networks in classification of steel grades based on non-destructive tests

A Beskopylny, A Lyapin, H Anysz, B Meskhi… - Materials, 2020 - mdpi.com
Assessment of the mechanical properties of structural steels characterizing their strength
and deformation parameters is an essential problem in the monitoring of structures that have …

Optimization of composition and technological factors for the lightweight fiber-reinforced concrete production on a combined aggregate with an increased coefficient of …

LR Mailyan, AN Beskopylny, B Meskhi, SA Stel'makh… - Applied Sciences, 2021 - mdpi.com
In recent years, developing lightweight concrete with both the necessary and sufficient
strength characteristics is essential in the construction industry. This article studies the …

Maximum response deep learning using Markov, retinal & primitive patch binding with GoogLeNet & VGG-19 for large image retrieval

KT Ahmed, S Jaffar, MG Hussain, S Fareed… - Ieee …, 2021 - ieeexplore.ieee.org
Smart and productive image retrieval from flexible image datasets is an unavoidable
necessity of the current period. Crude picture marks are imperative to mirror the visual …