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Comprehensive study on applications of artificial neural network in food process modeling
GVS Bhagya Raj, KK Dash - Critical reviews in food science and …, 2022 - Taylor & Francis
Artificial neural network (ANN) is a simplified model of the biological nervous system
consisting of nerve cells or neurons. The application of ANN to food process engineering is …
consisting of nerve cells or neurons. The application of ANN to food process engineering is …
A review on the utilized machine learning approaches for modeling the dynamic viscosity of nanofluids
Nanofluids are broadly applied in energy systems such as solar collector, heat exchanger
and heat pipes. Dynamic viscosity of the nanofluids is among the most important features …
and heat pipes. Dynamic viscosity of the nanofluids is among the most important features …
Recent advances in machine learning research for nanofluid-based heat transfer in renewable energy system
Nanofluids have gained significant popularity in the field of sustainable and renewable
energy systems. The heat transfer capacity of the working fluid has a huge impact on the …
energy systems. The heat transfer capacity of the working fluid has a huge impact on the …
[HTML][HTML] Fuzzy decision-making framework for explainable golden multi-machine learning models for real-time adversarial attack detection in Vehicular Ad-hoc …
This paper addresses various issues in the literature concerning adversarial attack detection
in Vehicular Ad-hoc Networks (VANETs). These issues include the failure to consider both …
in Vehicular Ad-hoc Networks (VANETs). These issues include the failure to consider both …
Machine learning regression-CFD models for the nanofluid heat transfer of a microchannel heat sink with double synthetic jets
A comprehensive analysis consisting of computational fluid dynamics (CFD) and machine
learning algorithms (MLAs) is conducted to study the effect of geometrical and operational …
learning algorithms (MLAs) is conducted to study the effect of geometrical and operational …
Prediction of nanofluids viscosity using random forest (RF) approach
Accurate estimation of viscosity, one of the most important thermo-physical properties of
nanofluids, is essential in heat transfer fluid applications in many industries. In this paper, for …
nanofluids, is essential in heat transfer fluid applications in many industries. In this paper, for …
Towards physician's experience: Development of machine learning model for the diagnosis of autism spectrum disorders based on complex T‐spherical fuzzy …
Autism spectrum disorders (ASD) are a diverse group of conditions characterized by
difficulty with social interaction and communication. ASD is expected to be a high‐risk …
difficulty with social interaction and communication. ASD is expected to be a high‐risk …
A comparison between the application of empirical and ANN methods for estimation of daily global solar radiation in Iran
The present study generally aims to provide a comparison between the performance and
suitability of different types of models for estimation of daily global solar radiation in Iran …
suitability of different types of models for estimation of daily global solar radiation in Iran …
Back propagation modeling of shear stress and viscosity of aqueous Ionic-MXene nanofluids
Back-propagation modeling of viscosity and shear stress of Ionic-MXene nanofluid is carried
out in this work. The data for Ionic-MXene nanofluid of 0.05, 0.1, and 0.2 mass concentration …
out in this work. The data for Ionic-MXene nanofluid of 0.05, 0.1, and 0.2 mass concentration …
Dependence of critical heat flux in vertical flow systems on dimensional and dimensionless parameters using machine learning
The critical heat flux (CHF) associated with the departure from nucleate boiling (DNB)
determines the design and safety aspects of two-phase flow boiling systems. Despite the …
determines the design and safety aspects of two-phase flow boiling systems. Despite the …