Improved prediction of fuel properties with near-infrared spectroscopy using a complementary sequential fusion of scatter correction techniques
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Improved prediction of fuel properties with near-infrared spectroscopy using a complementary sequential fusion of scatter correction techniques
Authors
Keywords
Multi-block data analysis, Data fusion, Spectroscopy, Preprocessing, Multivariate analysis, Fuel
Journal
TALANTA
Volume 223, Issue -, Pages 121693
Publisher
Elsevier BV
Online
2020-09-25
DOI
10.1016/j.talanta.2020.121693
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A spectra partition algorithm based on spectral clustering for interval variable selection
- (2020) Yinran Xiong et al. INFRARED PHYSICS & TECHNOLOGY
- Open-source python module for automated preprocessing of near infrared spectroscopic data
- (2020) Jari Torniainen et al. ANALYTICA CHIMICA ACTA
- Sequential preprocessing through ORThogonalization (SPORT) and its application to near infrared spectroscopy
- (2020) Jean-Michel Roger et al. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
- MBA-GUI: A chemometric graphical user interface for multi-block data visualisation, regression, classification, variable selection and automated pre-processing
- (2020) Puneet Mishra et al. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
- SPORT pre-processing can improve near-infrared quality prediction models for fresh fruits and agro-materials
- (2020) Puneet Mishra et al. POSTHARVEST BIOLOGY AND TECHNOLOGY
- VSN: Variable sorting for normalization
- (2019) Gilles Rabatel et al. JOURNAL OF CHEMOMETRICS
- Handheld near-infrared spectrometer for on-line monitoring of biodiesel production in a continuous process
- (2019) Rafaella Sales et al. FUEL
- Identification of petroleum profiles by infrared spectroscopy and chemometrics
- (2019) Betina P.O. Lovatti et al. FUEL
- Multivariate regression models obtained from near-infrared spectroscopy data for prediction of the physical properties of biodiesel and its blends
- (2019) Camilla L. Cunha et al. FUEL
- Multivariate calibration of spectroscopic sensors for postharvest quality evaluation: A review
- (2019) Wouter Saeys et al. POSTHARVEST BIOLOGY AND TECHNOLOGY
- Near infrared spectroscopy: A mature analytical technique with new perspectives – A review
- (2018) Celio Pasquini ANALYTICA CHIMICA ACTA
- A variable importance criterion for variable selection in near-infrared spectral analysis
- (2018) Jin Zhang et al. Science China-Chemistry
- Common and distinct components in data fusion
- (2017) Age K. Smilde et al. JOURNAL OF CHEMOMETRICS
- Predicting fuel properties using chemometrics: a review and an extension to temperature dependent physical properties by using infrared spectroscopy to predict density
- (2016) Zachariah Steven Baird et al. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
- Simple and Effective Way for Data Preprocessing Selection Based on Design of Experiments
- (2015) Jan Gerretzen et al. ANALYTICAL CHEMISTRY
- Pretreating near infrared spectra with fractional order Savitzky–Golay differentiation (FOSGD)
- (2015) Kai-Yi Zheng et al. CHINESE CHEMICAL LETTERS
- Quantification of biodiesel and adulteration with vegetable oils in diesel/biodiesel blends using portable near-infrared spectrometer
- (2015) Eduardo Maia Paiva et al. FUEL
- Determination of the oxidative stability of biodiesel using near infrared emission spectroscopy
- (2013) Francisco Senna Vieira et al. FUEL
- Breaking with trends in pre-processing?
- (2013) Jasper Engel et al. TRAC-TRENDS IN ANALYTICAL CHEMISTRY
- Near Infrared Spectroscopic Determination of Diesel Fuel Parameters Using Genetic Multivariate Calibration
- (2008) D. Özdemir PETROLEUM SCIENCE AND TECHNOLOGY
- Gasoline classification by source and type based on near infrared (NIR) spectroscopy data
- (2007) Roman M. Balabin et al. FUEL
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now