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Prediction of Rice Processing Loss Rate Based on GA-BP Neural Network

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成果类型:
会议论文
作者:
Yang, Hua;Li, Jian;Liu, Neng;Yi, Kecheng;Wang, Jing;...
通讯作者:
Yang, H
作者机构:
[Yi, Kecheng; Fu, Rou; Wang, Jing; Yang, Pengcheng; Yang, Hua; Xiang, Yunzhu; Yang, H; Hang, Tianyu; Li, Jian; Liu, Neng; Zhang, Jun] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430040, Peoples R China.
[Zhang, Tiancheng; Wang, Siyi] Wuhan BisiCloud Technol Co Ltd, Wuhan 430015, Peoples R China.
通讯机构:
[Yang, H ] W
Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430040, Peoples R China.
语种:
英文
关键词:
GA-BP neural network;Prediction model;Rice processing loss
期刊:
Communications in Computer and Information Science
ISSN:
1865-0929
年:
2024
卷:
2062
页码:
121-132
会议名称:
18th International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA)
会议论文集名称:
Communications in Computer and Information Science
会议时间:
DEC 15-17, 2023
会议地点:
Changsha, PEOPLES R CHINA
会议主办单位:
[Yang, Hua;Li, Jian;Liu, Neng;Yi, Kecheng;Wang, Jing;Fu, Rou;Zhang, Jun;Xiang, Yunzhu;Yang, Pengcheng;Hang, Tianyu] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430040, Peoples R China.^[Zhang, Tiancheng;Wang, Siyi] Wuhan BisiCloud Technol Co Ltd, Wuhan 430015, Peoples R China.
主编:
Pan, L Wang, Y Lin, J
出版地:
152 BEACH ROAD, #21-01/04 GATEWAY EAST, SINGAPORE, 189721, SINGAPORE
出版者:
SPRINGER-VERLAG SINGAPORE PTE LTD
ISBN:
978-981-97-2274-7; 978-981-97-2275-4
基金类别:
Ministry of Education's Industry-University Cooperatian and Education Project [220900786024216]; Educational Research Project in Hubei Province [2018368]; Graduate Workstation School-Enterprise Cooperation Project in Hubei Province; Horizontal school-enterprise cooperation project; Wuhan Polytechnic University School Established Research Project [XM2021015]
机构署名:
本校为第一且通讯机构
院系归属:
数学与计算机学院
摘要:
Food is closely related to national economy and people's livelihood. Rice is the largest grain crop in China, it is crucial to predict the loss rate of rice during processing to reduce food waste and ensure food security. This study first obtained the loss rate of rice processing through the recovery survey form of enterprises. Then, prediction was carried out using two common models: the BP neural network and multiple linear regression. Finally, the genetic algorithm was applied to optimize the BP neural network for further prediction and com-pared with the original models. The experimental r...

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