Add to ORKGThe implementation of artificial neural networks (ANNs) to the analysis of multivariate data is reviewed, with particular reference to the analysis of pyrolysis mass spectra. The need for and benefits of multivariate data analysis are explained followed by a discussion of ANNs and their optimisation. Finally, an example of the use of ANNs for the quantita-tive deconvolution of the pyrolysis mass spectra of Staphylococcus au reus mixed with Escherichia coli is demonstrated
An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced em...
Infrared absorption spectroscopy is a widely used tool to quantify and monitor compositions of gases...
Neutron activation analysis has been widely used for quantitative analysis. It can quantify elements...
Sixteen representatives of three morphologically distinct groups of streptomycetes were recovered fr...
Artificial neural networks (ANNs) are a method of machine learning (ML) that is now widely used in p...
The artificial neural networks (ANN) are very often applied in many areas of toxicology for the solv...
An artificial neural network was trained to distinguish between three putatively novel species of St...
Sixteen reference strains and thirteen fresh isolates of three putatively novel Streptomyces species...
Purpose: To develop an effective analytical method to distinguish old peels of Xinhui Pericarpium ci...
Artificial neural networks (ANNs) are non-linear computational tools suitable to a great host of pra...
There are two broadly-defined applications of artificial neural networks (ANNs) in SAR/QSAR modeling...
Artificial neural networks (ANNs) are a method of machine learning (ML) that is now widely used in p...
We investigate which of two Artificial Intelligence techniques is superior at making predictions abo...
This paper explores the use of Neural Networks as a novel approach in the implementation of spectral...
The pyrolytic behavior of lignocellulosic biomass is highly complex, and its kinetic behavior varies...
An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced em...
Infrared absorption spectroscopy is a widely used tool to quantify and monitor compositions of gases...
Neutron activation analysis has been widely used for quantitative analysis. It can quantify elements...
Sixteen representatives of three morphologically distinct groups of streptomycetes were recovered fr...
Artificial neural networks (ANNs) are a method of machine learning (ML) that is now widely used in p...
The artificial neural networks (ANN) are very often applied in many areas of toxicology for the solv...
An artificial neural network was trained to distinguish between three putatively novel species of St...
Sixteen reference strains and thirteen fresh isolates of three putatively novel Streptomyces species...
Purpose: To develop an effective analytical method to distinguish old peels of Xinhui Pericarpium ci...
Artificial neural networks (ANNs) are non-linear computational tools suitable to a great host of pra...
There are two broadly-defined applications of artificial neural networks (ANNs) in SAR/QSAR modeling...
Artificial neural networks (ANNs) are a method of machine learning (ML) that is now widely used in p...
We investigate which of two Artificial Intelligence techniques is superior at making predictions abo...
This paper explores the use of Neural Networks as a novel approach in the implementation of spectral...
The pyrolytic behavior of lignocellulosic biomass is highly complex, and its kinetic behavior varies...
An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced em...
Infrared absorption spectroscopy is a widely used tool to quantify and monitor compositions of gases...
Neutron activation analysis has been widely used for quantitative analysis. It can quantify elements...