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Updated: Sep 15, 2025

A Cost-effective and Reliable Method to Predict Mechanical Stress in Single-use and Standard Pumps
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使用人工神经网络 (ANN) 模型和半经验相关性,预测L形脉冲打包列中的滴量分布和平均滴量

Ali Ravandeh1, Sajad Khooshechin2

  • 1Department of Chemical Engineering, Shiraz University, Shiraz, 71345, Iran.

Scientific reports
|July 16, 2025
PubMed
概括

人工神经网络 (ANN) 准确预测提取列中的下降大小,优于传统模型. 较高的脉冲强度降低了对滴滴大小的界面张力效应.

关键词:
人工神经网络的人工神经网络滴量 大小 滴量 大小一个L形的柱子.脉冲打包列的脉冲打包列是一个非常简单的列.

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