Quantitative Identification Method for Glass Panel Defects Using Microwave Detection Based on the CSAPSO-BP Neural Network

To address the problem of the quantitative identification of glass panel surface defects, a new method combining the chaotic simulated annealing particle swarm algorithm (CSAPSO) and the BP neural network is proposed for the quantitative evaluation of microwave detection signals of glass panel defec...

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Detalles Bibliográficos
Autores principales: Fang, Jun, Deng, Zhiyang, Tu, Jun, Song, Xiaochun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921799/
https://www.ncbi.nlm.nih.gov/pubmed/36772137
http://dx.doi.org/10.3390/s23031097

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921799/
https://www.ncbi.nlm.nih.gov/pubmed/36772137
http://dx.doi.org/10.3390/s23031097

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