Search
Now showing items 71-80 of 90
Predictive ANN models for varying filler content for cotton fiber/PVC composites based on experimental load displacement curves
(
Elsevier Ltd
, 2020 , Article)
In this paper, artificial neural network (ANN) models are developed to predict the load-displacement curves for better understanding the behavior of cotton fiber/polyvinyl chloride (PVC) composites. Series of experiments ...
Data-driven modeling to predict the load vs. displacement curves of targeted composite materials for industry 4.0 and smart manufacturing
(
Elsevier Ltd
, 2021 , Article)
This work presents an approach for smart manufacturing focusing on Industry 4.0 to predict the load vs. displacement curve of targeted cotton fiber/Polypropylene (PP) composite materials while complying with the required ...
Machine learning for prediction of the uniaxial compressive strength within carbonate rocks
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
The Uniaxial Compressive Strength (UCS) is an essential parameter in various fields (e.g., civil engineering, geotechnical engineering, mechanical engineering, and material sciences). Indeed, the determination of UCS in ...
On the Investigation of Monthly River Flow Generation Complexity Using the Applicability of Machine Learning Models
(
Hindawi Limited
, 2021 , Article)
Streamflow is associated with several sources on nonstationaries and hence developing machine learning (ML) models is always the motive to provide a reliable methodology to understand the actual mechanism of streamflow. ...
The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar
(
Elsevier Ltd
, 2022 , Article)
The goal of this study is to use machine-learning (ML) techniques and empirical big data to examine the influence of the COVID-19 pandemic on electricity usage and electricity demand forecasting accuracy in buildings in ...
Use of machine learning to assess factors affecting progression, retention, and graduation in first-year health professions students in Qatar: a longitudinal study
(
BioMed Central Ltd
, 2023 , Article)
Background: Across higher education, student retention, progression, and graduation are considered essential elements of students’ academic success. However, there is scarce literature analyzing these attributes across ...
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
(
Elsevier
, 2023 , Article)
Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing skills in children, resulting in poor writing abilities. Poor or underdeveloped writing skills in children can negatively impact ...
A new approach to predicting cryptocurrency returns based on the gold prices with support vector machines during the COVID-19 pandemic using sensor-related data
(
MDPI
, 2021 , Article)
In a real-world situation produced under COVID-19 scenarios, predicting cryptocurrency returns accurately can be challenging. Such a prediction may be helpful to the daily economic and financial market. Unlike forecasting ...
Modeling of permeability impairment dynamics in porous media: A machine learning approach
(
Elsevier
, 2023 , Article)
The prediction of clogging and permeability impairment dynamics in porous media is crucial for the optimization of various industrial and natural processes. This paper presents a novel machine learning-based approach for ...
Influence of Reaction Time in the Emotional Response of a Companion Robot to a Child’s Aggressive Interaction
(
springer link
, 2020 , Article)
The quality of a companion robot’s reaction is important to make it acceptable to the users and to sustain interactions. Furthermore, the robot’s reaction can be used to train socially acceptable behaviors and to develop ...