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Neutron spectrum unfolding code based on iterative method combined with artificial neural networks for bonner sphere spectrometer
In this work, an improved neutron spectrum unfolding code “Artificial Neural Network Iterative” (ANN_Iter), which utilizes the iterative method...
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Estimation of Net Heat of Combustion of Light Kerosene Distillates Using Artificial Neural Networks
AbstractIn this study, six feedforward neural network models were developed to estimate the net heat of combustion of light kerosene distillates....
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Assessment of artificial neural networks to predict red colorant production by Talaromyces amestolkiae
Consumer choice is typically influenced by color, leading to an increase in the use of artificial colorants by industry. However, several artificial...
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Non-linearity and Artificial Neural Networks. Multi-layer Perceptron
An introduction to multi-layer perceptron artificial neural networks is presented. The optimization of the relevant network parameters using...
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Artificial neural networks for NAA: proof of concept on data analysed with k0-based software
Artificial intelligence methods such as artificial neural networks, Bayesian networks, genetic algorithms, and others, have shown great potential for...
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Prediction of the Fatty Acid Profiles of Iberian Pig Products by Near Infrared Spectroscopy: A Comparison Between Multiple Regression Tools and Artificial Neural Networks
In this study, the feasibility of predicting the lipid profiles of Iberian ham and shoulder samples by using near infrared (NIR) spectroscopy was...
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Checking the performance of feed-forward and cascade artificial neural networks for modeling the surface tension of binary hydrocarbon mixtures
To estimate the surface tension of liquid hydrocarbon mixtures as an essential thermophysical property, artificial neural networks (AANs) are used....
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Prediction of Electromagnetic Properties Using Artificial Neural Networks for Oil Recovery Factors
AbstractThe most important parameter in the oil and gas industry is the recovery factor (RF). Higher oil consumption has resulted in a rise in global...
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Artificial Neural Networks for Modelling the Degradation of Emerging Contaminants Process
Diclofenac sodium is an emerging contaminant that can be harmful for ecology and human health. This substance can be degraded by a heterogeneous...
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Carbon Dioxide Adsorption Study on Rice Husk Activated Carbons by Artificial Neural Network (ANN)
AbstractIn this study, the effects of artificial neural networks on CO 2 adsorption on several types of rice husk activated carbon samples are...
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Artificial neural networks in the modeling of the catalytic activity of a biosensor composed of conjugated polymers and urease
Thin films of conjugated polymer and enzyme can be used to unravel the interaction between components in a biosensor. Using artificial neural...
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Artificial neural networks and their utility in fitting potential energy curves and surfaces and related problems
Artificial intelligence (AI) and machine learning (ML) methods have touched practically all aspects of our life. Their utility ranges from separating...
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Deep Study on Fouling Modelling of Ultrafiltration Membranes Used for OMW Treatment: Comparison Between Semi-empirical Models, Response Surface, and Artificial Neural Networks
Olive oil production generates a large amount of wastewater called olive mill wastewater. This paper presents the study of the effect of...
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Analytically Supported Hybrid Photonic–plasmonic Crystal Design Using Artificial Neural Networks
An analytical and numerical study of hybrid photonic–plasmonic crystals is presented. The proposed theoretical model describes a system composed of a...
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Application of Artificial Neural Networks for the Analysis of Data on Liquid–Liquid Equilibrium in Three-Component Systems
AbstractThe potential use of artificial neural networks to describe liquid–liquid phase equilibria in ternary systems under polythermal conditions is...
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Determination of Sulfacetamide in Blood and Urine Using PBS Quantum Dots Sensor and Artificial Neural Networks
AbstractFluorescent chemical sensors have been proposed to detect drugs by increasing or shutting down the fluorescence emission and absorption....
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Non-linearity and Artificial Neural Networks. Radial Basis Functions and Kernel Partial Least-Squares
An introduction to calibration of non-linear systems with artificial neural networks is provided. Detailed information is given on calibration using...
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Human immunoglobulin G adsorption in hydrophobic ligands: equilibrium data, isotherm modelling and prediction using artificial neural networks
This work aimed to evaluate the adsorption of human Immunoglobulin G in the hydrophobic interaction adsorbents: Phenyl Sepharose 6 Fast Flow High Sub...
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Equilibrium Moisture Content and Dioxide Carbon Monitoring in Real-Time to Predict the Quality of Corn Grain Stored in Silo Bags using Artificial Neural Networks
The determination of equilibrium moisture content, associated with measuring the respiration of the grain mass in real time, is a possible indicator...
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Mathematical modeling of drying kinetics of ground Açaí (Euterpe oleracea) kernel using artificial neural networks
The utilization of Açaí residues holds significant economic and environmental importance in Brazil. The drying technique is an alternative for...
