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

Published in:	Scientific Reports
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
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