Prediction of Grain Porosity Based on GWO-BP Neural Network and Grain Compression Experiment

Prediction of Grain Porosity Based on GWO-BP Neural Network and Grain Compression Experiment

Porosity is a key parameter that affects the heat and moisture transfer within a grain pile. In order to investigate the distribution law of porosity in bulk grain piles in grain silos, grain compression experiment was carried out to obtain the porosity of different grain types under different moist...

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Bibliographic Details
Main Authors: CHEN Jia-hao, LI Jia-xin, ZHENG De-qian, YIN Jun, HUANG Hai-rong, GE Meng-meng, ZHANG Jia-yi
Format: Article
Language:English
Published: Academy of National Food and Strategic Reserves Administration 2024-03-01
Series:Liang you shipin ke-ji
Subjects:
gwo-bp model
grain porosity
compression test
prediction
Online Access:http://lyspkj.ijournal.cn/lyspkj/article/abstract/20240225

Internet

http://lyspkj.ijournal.cn/lyspkj/article/abstract/20240225

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