Analysis of the Oil Content of Rapeseed Using Artificial Neural Networks Based on Near Infrared Spectral Data
Joint Authors
Li, Hao
Yang, Dazuo
Cao, Chenchen
Chen, Fudi
Zhou, Yibing
Xiu, Zhilong
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-22
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
The oil content of rapeseed is a crucial property in practical applications.
In this paper, instead of traditional analytical approaches, an artificial neural network (ANN) method was used to analyze the oil content of 29 rapeseed samples based on near infrared spectral data with different wavelengths.
Results show that multilayer feed-forward neural networks with 8 nodes (MLFN-8) are the most suitable and reasonable mathematical model to use, with an RMS error of 0.59.
This study indicates that using a nonlinear method is a quick and easy approach to analyze the rapeseed oil’s content based on near infrared spectral data.
American Psychological Association (APA)
Yang, Dazuo& Li, Hao& Cao, Chenchen& Chen, Fudi& Zhou, Yibing& Xiu, Zhilong. 2014. Analysis of the Oil Content of Rapeseed Using Artificial Neural Networks Based on Near Infrared Spectral Data. Journal of Spectroscopy،Vol. 2014, no. 2014, pp.1-5.
https://search.emarefa.net/detail/BIM-1043148
Modern Language Association (MLA)
Yang, Dazuo…[et al.]. Analysis of the Oil Content of Rapeseed Using Artificial Neural Networks Based on Near Infrared Spectral Data. Journal of Spectroscopy No. 2014 (2014), pp.1-5.
https://search.emarefa.net/detail/BIM-1043148
American Medical Association (AMA)
Yang, Dazuo& Li, Hao& Cao, Chenchen& Chen, Fudi& Zhou, Yibing& Xiu, Zhilong. Analysis of the Oil Content of Rapeseed Using Artificial Neural Networks Based on Near Infrared Spectral Data. Journal of Spectroscopy. 2014. Vol. 2014, no. 2014, pp.1-5.
https://search.emarefa.net/detail/BIM-1043148
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1043148