In order to improve the feature extraction ability of nanofibers, a feature detection method based on non-linear mapping pattern recognition is proposed. The cluster–cluster hybrid molecular reconstruction method is used to deal with the spatial spectrum beamforming of nanofiber features, and the recursive graph analysis method is used to decompose the association rule features of nanofibers to realize the non-linear mapping pattern recognition of nanofiber features. Combined with the related attribute-clustering method, the characteristics of nanofibers are classified and identified to achieve the optimization of nanofiber feature detection. The simulation results show that the method has high accuracy, good performance of pattern recognition of non-linear mapping and good ability of accurate recognition of the crystal structure characteristics of nanofibers.
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22 March 2021
Research Article|
January 15 2021
Nanocrystalline collagen-based bone materials in skeletal optimization in patients Available to Purchase
Yanshan Yu, MSc;
Yanshan Yu, MSc
Professor
Sports Department, Xi’an Polytechnic University, Xi’an, China; Educational Development Department, Harper Adams University, Newport, UK
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Lijuan Wang, MSc;
Lijuan Wang, MSc
Professor
Sports Department, Hebei Vocational College of Politics and Law, Shijiazhuang, China
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Pingjun Ma, MSc
Department of Physical Education, Northwest A&F University, Xianyang, China
(corresponding author: mpj8965@nwsuaf.edu.cn)
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(corresponding author: mpj8965@nwsuaf.edu.cn)
Publisher: Emerald Publishing
Received:
December 26 2019
Accepted:
December 18 2020
Online ISSN: 2045-984X
Print ISSN: 2045-9831
ICE Publishing: All rights reserved
2021
Nanomaterials and Energy (2021) 10 (1): 9–16.
Article history
Received:
December 26 2019
Accepted:
December 18 2020
Citation
Yu Y, Wang L, Ma P (2021), "Nanocrystalline collagen-based bone materials in skeletal optimization in patients". Nanomaterials and Energy, Vol. 10 No. 1 pp. 9–16, doi: https://doi.org/10.1680/jnaen.20.00005
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