Performance control study of interleaved meltblown nonwoven materials
DOI:
https://doi.org/10.54097/hset.v52i.9599Keywords:
Typical correlation analysis, Neural Networks Bayesian regularization, Multiple regression model, Multi-objective planning model.Abstract
Meltblown nonwoven material is an important raw material for mask production, and in order to optimize the product performance, this paper conducts a relevant study on its performance control. A typical correlation analysis model is constructed to study the effect of interpolation on structural variables and product performance variation, and a four-layer BP neural network model is constructed for predictive analysis to study the relationship between process parameters and structural variables. This paper maximizes the filtration efficiency and minimizes the filtration resistance while taking into account all conditions and requirements
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