Application of Support Vector Regression for Simultaneous Modelling of near Infrared Spectra from Multiple Process Steps

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http://www.wikidata.org/entity/Q57534330

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im Jahr 2015 veröffentlichter wissenschaftlicher Artikel

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wetenschappelijk artikel

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наукова стаття, опублікована в січні 2015

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name

Application of Support Vector ...... ra from Multiple Process Steps

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Application of Support Vector ...... ra from Multiple Process Steps

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type

Item

label

Application of Support Vector ...... ra from Multiple Process Steps

@en

Application of Support Vector ...... ra from Multiple Process Steps

@nl

prefLabel

Application of Support Vector ...... ra from Multiple Process Steps

@en

Application of Support Vector ...... ra from Multiple Process Steps

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P1476

Application of Support Vector ...... ra from Multiple Process Steps

@en

P2093

Eizo Taira

http://www.w3.org/2001/XMLSchema#string

Morten Arendt Rasmussen

http://www.w3.org/2001/XMLSchema#string

Rasmus Bro

http://www.w3.org/2001/XMLSchema#string

Rikke Tange

http://www.w3.org/2001/XMLSchema#string

P2860

Development of a robust calibration model for nonlinear in-line process data

Effect of temperature variation on the visible and near infrared spectra of wine and the consequences on the partial least square calibrations developed to measure chemical composition.

Support vector machine regression (SVR/LS-SVM) - an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data

Interpolation and extrapolation problems of multivariate regression in analytical chemistry: benchmarking the robustness on near-infrared (NIR) spectroscopy data.

Chemometrics-based process analytical technology (PAT) tools: applications and adaptation in pharmaceutical and biopharmaceutical industries.

Short-wavelength near-infrared spectra of sucrose, glucose, and fructose with respect to sugar concentration and temperature.

Multivariate calibration with least-squares support vector machines.

Support vector machines for classification and regression.

Prediction of protein retention times in anion-exchange chromatography systems using support vector regression.

Handling intrinsic non-linearity in near-infrared reflectance spectroscopy

P304

75-84

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P31

scholarly article

P356

10.1255/JNIRS.1149

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P433

http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

P577

2015-01-01T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P921

support vector machine

infrared spectroscopy