An intelligent moisture prediction method for tobacco drying process using a multi-hierarchical convolutional neural network-Reference-Cited by-同舟云学术

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An intelligent moisture prediction method for tobacco drying process using a multi-hierarchical convolutional neural network

Published:2021-02-12 Issue:9 Volume:40 Page:1791-1803
ISSN:0737-3937
Container-title:Drying Technology
language:en
Short-container-title:Drying Technology

Author:

Mu Liangliang¹²,Bi Suhuan³,Yu Shusong⁴,Liu Xiuyan³,Ding Xiangqian⁴

Affiliation:

1. B-Soft, Hangzhou, China

2. School of Management, Shandong University, Jinan City, China

3. School of Information and Control Engineering, Qingdao University of Technology, Qingdao City, China

4. College of Information Science and Engineering, Ocean University of China, Qingdao City, China

Publisher

Informa UK Limited

Subject

Physical and Theoretical Chemistry,General Chemical Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/07373937.2021.1876722

Reference36 articles.

1. Study on the Effect of Cut Tobacco Drying on the Pyrolysis and Combustion Properties

2. Validation of a Model of an Expanding Superheated Steam Flash Dryer for Cut Tobacco Based on Processing Data

3. Cubic-RBF-ARX modeling and model-based optimal setting control in head and tail stages of cut tobacco drying process

4. Drying process of tobacco leaves by using a fuzzy controller

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1. Enhancing prior-knowledge-based control with deep attention neural network for outlet moisture content of cut-tobacco;Drying Technology;2024-07-17

2. The Significance of Industry 4.0 Technologies in Enhancing Various Unit Operations Applied in the Food Sector: Focus on Food Drying;Food and Bioprocess Technology;2024-06-10

3. Double-Loop-Optimization-Based Joint Parameter Tuning for Dynamic Matrix Control With Validation in Intelligent Cigarette Drying Process;IEEE Transactions on Industrial Informatics;2024-05

4. Analysis of energy consumption of tobacco drying process based on industrial big data;Drying Technology;2023-11-30

5. Prediction of the capacitance of the corn drying process parameter using adaptive- neuro-fuzzy intelligent technique with experimental validation;Drying Technology;2023-10-23

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