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Predictive method for poultry carcass visceral dimensions using 3D point cloud and Genetic Algorithm-based wavelet neural network

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成果类型:
期刊论文
作者:
Zhu, Zhengwei;Chen, Yan;Cai, Lu;Yang, Jinzhou;Wen, Ke;...
通讯作者:
Chen, Y
作者机构:
[Bao, Jingjing; Hu, Zhigang; Wen, Ke; Yang, Jinzhou; Fu, Dandan; Cai, Lu; Chen, Yan; Zhu, Zhengwei] Wuhan Polytech Univ, Coll Mech Engn, Wuhan 430048, Hubei, Peoples R China.
通讯机构:
[Chen, Y ] W
Wuhan Polytech Univ, Coll Mech Engn, Wuhan 430048, Hubei, Peoples R China.
语种:
英文
关键词:
3D point cloud;Genetic algorithm-based wavelet neural network;Mean absolute percentage error;Poultry viscera;Root mean square error
期刊:
Poultry Science
ISSN:
0032-5791
年:
2025
卷:
104
期:
1
页码:
104516
机构署名:
本校为第一且通讯机构
院系归属:
机械工程学院
摘要:
In order to avoid damaging viscera during poultry evisceration and enhance the economic value of poultry products, this paper proposes a predictive method for poultry carcass visceral dimensions based on 3D point cloud and a Genetic Algorithm-based Wavelet Neural Network (GA-WNN). In this study, a data set of poultry carcasses was obtained through the use of 3D point cloud scanning equipment combined with reverse engineering software. The inputs and predicted targets of the model were determined through correlation analysis of various carcass dimensions. Then, a prediction model of poultry vis...

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