Artificial Neural Networks (ANNs) for Spectral Interference Correction Using a Large-Size Spectrometer and ANN-Based Deep Learning for a Miniature One

Mohua, G. A.; Zhang, Z. Li, X.; Karanassios, Vassili

doi:10.5772/intechopen.71039

Artificial Neural Networks (ANNs) for Spectral Interference Correction Using a Large-Size Spectrometer and ANN-Based Deep Learning for a Miniature One

dc.creator	Mohua, G. A.
dc.creator	Zhang, Z. Li, X.
dc.creator	Karanassios, Vassili
dc.date.accessioned	2021-01-20T20:30:11Z
dc.date.available	2021-01-20T20:30:11Z
dc.date.created	2017-12-20
dc.description.abstractenglish	Artificial neural networks (ANNs) are evaluated for spectral interference correction using simulated and experimentally obtained spectral scans. Using the same data set (where possible), the predictive ability of shallow depth ANNs was validated against partial least squares (PLS, a traditional chemometrics method). Spectral interference (in the form of overlaps between spectral lines) is a key problem in large-size, long focal length inductively coupled plasma-optical emission spectrometry (ICP-OES). Unless corrected, spectral interference can be sufficiently severe to the point of preventing precise and accurate analytical determinations. In miniaturized, microplasma-based optical emission spectrometry with a portable, short focal length spectrometer (having poorer resolution than its large-size counterpart), spectral interference becomes even more severe. To correct it, we are evaluating use of deep learning ANNs. Details are provided in this chapter.	spa
dc.format.extent	25 páginas	spa
dc.format.mimetype	text/html	spa
dc.identifier.doi	10.5772/intechopen.71039
dc.identifier.other	https://www.intechopen.com/books/advanced-applications-for-artificial-neural-networks/artificial-neural-networks-anns-for-spectral-interference-correction-using-a-large-size-spectrometer
dc.identifier.uri	https://hdl.handle.net/20.500.12010/16802
dc.language.iso	eng	spa
dc.publisher	IntechOpen	spa
dc.relation.references	Z. Li, X. Zhang, GA Mohua y Vassili Karanassios (20 de diciembre de 2017). Redes neuronales artificiales (ANN) para la corrección de interferencias espectrales utilizando un espectrómetro de gran tamaño y aprendizaje profundo basado en ANN para uno en miniatura, Aplicaciones avanzadas para redes neuronales artificiales, Adel El-Shahat, IntechOpen, DOI: 10.5772 / intechopen.71039.	spa
dc.rights.accessrights	info:eu-repo/semantics/openAccess	spa
dc.rights.creativecommons	https://creativecommons.org/licenses/by-nc/4.0/legalcode
dc.rights.local	Abierto (Texto Completo)	spa
dc.subject	Biología	spa
dc.subject.lemb	Redes neuronales artificiales	spa
dc.subject.lemb	Inteligencia artificial -- Robótica	spa
dc.subject.lemb	Espectrometría de emisión óptica portátil	spa
dc.title	Artificial Neural Networks (ANNs) for Spectral Interference Correction Using a Large-Size Spectrometer and ANN-Based Deep Learning for a Miniature One	spa
dc.type.coar	http://purl.org/coar/resource_type/c_2f33	spa

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