An advanced CNN-attention model with IFTTA optimization for prediction air consumption of relay nozzles

An advanced CNN-attention model with IFTTA optimization for prediction air consumption of relay nozzles

Abstract The air jet loom is an energy-intensive machine, it is significantly reducing air consumption of relay nozzles for saving energy of air compressor. This paper proposes a Convolutional Neural Network (CNN)-Attention regression model to predict air consumption of the relay nozzle, enhancing a...

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Bibliographic Details
Main Authors: Shen Min, Shao Ning, Cao Yongbo, Xiong Xiaoshuang, Yang Xuezheng, Wang Zhen, Yu Lianqing
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Air consumption
Relay nozzles
Air-jet loom
CNN-attention
Improved football team training algorithm (IFTTA)
Online Access:https://doi.org/10.1038/s41598-025-94418-y
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https://doi.org/10.1038/s41598-025-94418-y

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