A study on Machine Learning Approaches for Predicting and Analyzing the Drying Process in the Textile Industry

Ke Haur Taur, Xiang Yun Deng, Mi Huo Chou, Jing Wei Chen, Yi Hsiu Lee, Wen June Wang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

6 引文 斯高帕斯(Scopus)

摘要

The main objective of this paper is to establish an output/input relationship model based on machine learning for the fabric drying process of a general textile factory. The scenario of the fabric drying process involves a conveyor belt that drives the fabric through eight drying boxes, and the targeted metric of the post-drying fabric is the moisture content rate. This paper is composed of two main parts. The first part is to explain that how to select a predictive model measuring the output performance of the setting machine. The second part discusses the optimization of energy-saving parameters of multiple models chosen in the first part. This paper will introduce some techniques such as neural networks and machine learning algorithms to find the most suitable output/input relationship model, or so called 'drying process quality prediction model', for future development of energy saving.

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主出版物標題2019 International Automatic Control Conference, CACS 2019
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728138466
DOIs
出版狀態已出版 - 11月 2019
事件2019 International Automatic Control Conference, CACS 2019 - Keelung, Taiwan
持續時間: 13 11月 201916 11月 2019

出版系列

名字2019 International Automatic Control Conference, CACS 2019

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???event.eventtypes.event.conference???2019 International Automatic Control Conference, CACS 2019
國家/地區Taiwan
城市Keelung
期間13/11/1916/11/19

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