Energy Attenuation Prediction of Dye-Doped PMMA Microfibers by Backpropagation Neural Network
To figure out the energy attenuation of micro/nanofibers (MNFs) more flexibly and conveniently, a backpropagation neural network (BPNN) is proposed to forecast the output intensity of rhodamine B (RhB) doped polymer microfibers (PMFs). According to the diameter, doping concentration, and...
Saved in:
| Main Authors: | Hang Yu, Juan Liu, Jinjin Han, Minghui Chen, Mingjun Ke, Zhili Lin, Zhijun Wu, Jixiong Pu, Xining Zhang, Hao Dai |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
|
| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9706252/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Quantitative Analysis of Structural Parameters Importance of Helical Temperature Microfiber Sensor by Artificial Neural Network
by: Juan Liu, et al.
Published: (2021-01-01) -
A Highly Sensitive Magnetic Field Sensor Based on a Tapered Microfiber
by: Zelong Ma, et al.
Published: (2018-01-01) -
Specificity of implementing the electrospinning of polymeric nano- and microfiber materials
by: V. A. Kozlov, et al.
Published: (2011-06-01) -
Integration Method with Backpropagation
by: Nidhal AL-Assady, et al.
Published: (2005-06-01) -
Comparison of Chondrocyte Behaviors Between Silk Microfibers and Polycaprolactone Microfibers in Tissue Engineering and Regenerative Medicine Applications
by: Guang-Zhen Jin
Published: (2024-11-01)