Predicting Ceramic Wool Diameter by Motor Frequency Using Improved BP Neural Network
نویسندگان
چکیده
Ceramic wool was prepared by the melt-spinning method, and diameter main factor severely affecting performance of final product which difficult to check online. The current study discusses approximate simulation fiber formation presents a fast precision measuring method predict ceramic using an improved Back-Propagation (BP) neural network. Particle Swarm Optimizer (PSO) employed optimize network structure for its presentation relationship between motor frequency spinning wheel diameter. superiority this demonstrated experiment compared with least square (LSM). mean measurement error PSO-BP 0.471%, lower than that LSM. presented very valuable predicting diameter, networks could solve nonlinear problems successfully, certified actual prediction
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2022
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app13010226