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Performance prediction method based on Liang-Kleeman information flow and wood tracheid morphology

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成果类型:
期刊论文
作者:
Huang, Jiahui;Kuang, Zhufang;Ma, Jingchao;Fang, Yixuan
通讯作者:
Kuang, ZF
作者机构:
[Huang, Jiahui] Cent South Univ Forestry & Technol, Sch Mat Sci & Engn, Changsha, Peoples R China.
[Kuang, Zhufang; Ma, Jingchao; Fang, Yixuan] Cent South Univ Forestry & Technol, Sch Comp & Informat Engn, Changsha, Peoples R China.
通讯机构:
[Kuang, ZF ] C
Cent South Univ Forestry & Technol, Sch Comp & Informat Engn, Changsha, Peoples R China.
语种:
英文
关键词:
Aspect ratio;Compressive strength;Morphology;Production efficiency;Scanning electron microscopy;Tensile strength;Time series analysis;Wood;Causal influences;Information flows;Liang kleeman information flow;Non destructive;Performance prediction;Prediction methods;Production efficiency;Production process;Wood industry;Wood tracheid;Forecasting
期刊:
Materials Today Communications
ISSN:
2352-4928
年:
2024
卷:
39
页码:
108620
基金类别:
This work was supported in part by the National Natural Science Foundation of China under Grants Nos. 62072477, 61309027, 61702562 and 61702561, the Hunan Provincial Natural Science Foundation of China under Grants No. 2018JJ3888, the Hunan Key Laboratory of Intelligent Logistics Technology 2019TP1015.
机构署名:
本校为第一且通讯机构
院系归属:
材料科学与工程学院
计算机与信息工程学院
摘要:
In order to improve the production efficiency of the wood industry and achieve intelligent feedback control in production processes, non-destructive online prediction of performance is crucial. With the increasing maturity of nanotechnology, the use of scanning electron microscopy (SEM) is becoming increasingly frequent. The Liang Kleeman (L-K) information flow theory is a quantitative causal analysis method based on time series data, which has the advantage of fast calculation. In order to predict the mechanical properties of wood in real-time...

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