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

被引：0

作者：

Yang, Hua ^{[1
]}

Li, Jian ^{[1
]}

Liu, Neng ^{[1
]}

Yi, Kecheng ^{[1
]}

Wang, Jing ^{[1
]}

Fu, Rou ^{[1
]}

Zhang, Jun ^{[1
]}

Xiang, Yunzhu ^{[1
]}

Yang, Pengcheng ^{[1
]}

Hang, Tianyu ^{[1
]}

Zhang, Tiancheng ^{[2
]}

Wang, Siyi ^{[2
]}

机构：

[1] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430040, Peoples R China

[2] Wuhan BisiCloud Technol Co Ltd, Wuhan 430015, Peoples R China

来源：

BIO-INSPIRED COMPUTING: THEORIES AND APPLICATIONS, PT 2, BIC-TA 2023 | 2024年 / 2062卷

关键词：

GA-BP neural network; Prediction model; Rice processing loss;

D O I：

10.1007/978-981-97-2275-4_10

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

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 results showed that the GA-BP model had higher prediction accuracy and smaller error compared to the first two models. It is valuable in reducing processing losses and maintaining food security.

引用

页码：121 / 132

页数：12

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