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Predictive ANN models for varying filler content for cotton fiber/PVC composites based on experimental load displacement curves
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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 ...
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. ...
Netizens' behavior towards a blockchain-based esports framework: a TPB and machine learning integrated approach
(
Emerald Publishing
, 2021 , Article)
Purpose: Based on the concepts confined in Ajzen's theory of planned behavior (TPB), this study investigates users' attitudes towards adoption of a blockchain-based framework in the esports industry that proposes a scheme ...
An optimal uplink traffic offloading algorithm via opportunistic communications based on machine learning
(
Springer
, 2020 , Article)
Opportunistic communications as an efficient traffic offloading method can be used to offload uplink traffic of cellular networks to Wi-Fi networks. However, because of its contact pattern (contact frequency and contact ...
Fault and performance management in multi-cloud virtual network services using AI: A tutorial and a case study
(
Elsevier B.V.
, 2019 , Article)
Carriers find Network Function Virtualization (NFV) and multi-cloud computing a potent combination for deploying their network services. The resulting virtual network services (VNS) offer great flexibility and cost advantages ...
Power transformer health condition evaluation: A deep generative model aided intelligent framework
(
Elsevier Ltd
, 2023 , Article)
This paper presents a deep generative model-aided intelligent framework for effective health condition evaluation of power grid transformers. The health assessment of a power transformer is required to guarantee the stable ...
RF-based drone detection and identification using deep learning approaches: An initiative towards a large open source drone database
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Elsevier B.V.
, 2019 , Article)
The omnipresence of unmanned aerial vehicles, or drones, among civilians can lead to technical, security, and public safety issues that need to be addressed, regulated and prevented. Security agencies are in continuous ...
Modeling of forward osmosis process using artificial neural networks (ANN) to predict the permeate flux
(
Elsevier
, 2020 , Article)
Artificial neural networks (ANN) are black box models that are becoming more popular than transport-based models due to their high accuracy and less computational time in predictions. The literature shows a lack of ANN ...
Data fusion strategies for energy efficiency in buildings: Overview, challenges and novel orientations
(
Elsevier
, 2020 , Article)
Recently, tremendous interest has been devoted to develop data fusion strategies for energy efficiency in buildings, where various kinds of information can be processed. However, applying the appropriate data fusion strategy ...