Moisture Content Prediction of Sugi Wood Drying Using Deep LSTM AE Minimizing Perturbed Error-Reference-Cited by-同舟云学术

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Moisture Content Prediction of Sugi Wood Drying Using Deep LSTM AE Minimizing Perturbed Error

Published:2023-10-01 Issue: Volume:8 Page:3756-3762
ISSN:
Container-title:2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
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Author:

Wang Ting¹,Ng Wing W. Y.²,Zhang Mingyang²,Zhang Xueli²,Zhang Jianjun²,Deng Mingcong³

Affiliation:

1. School of Medicine, South China University of Technology,Department of Radiology Guangzhou First People's Hospital,Guangzhou,China

2. School of Computer Science and Engineering, South China University of Technology,Guangzhou,China

3. Tokyo University of Agriculture and Technology,Department of Electrical and Electronic Engineering,Tokyo,Japan

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10391856/10393862/10394502.pdf?arnumber=10394502

Reference17 articles.

1. Thermal degradation of beech wood with thermogravimetry/Fourier transform infrared analysis

2. Moisture content prediction of wood drying process using svm-based model;Wen;INT J INNOV COMPUT I,2012

3. System Identification of Wood Drying Process Based on ARMAX Model

4. New density-independent moisture measurement using microwave phase shifts at two frequencies

5. Time Horizon-Based Model Predictive Volt/VAR Optimization for Smart Grid Enabled CVR in the Presence of Electric Vehicle Charging Loads

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