基于改进郊狼算法与极限学习机的工业金刚石检测

TP183%TP391; 为了提高工业金刚石的检测效率、保障产品质量,提出一种基于改进郊狼算法与极限学习机的工业金刚石检测方法.将工业金刚石视频图像按照一定时间序列分解为一组较为平稳的、形态单一的二维图像数据;利用深度卷积网络Inception-V3对多视角二维图像数据建立预测模型;在此基础上,以预测结果为输入构建极限学习机模型,并利用反向学习和莱维飞行改进的郊狼算法优化极限学习机输入权值和阈值,提高工业金刚石模型的检测精度.最后将该模型的检测结果与基本极限学习机、差分进化算法、粒子群优化算法和基本郊狼算法优化的极限学习机模型检测结果比较表明,该模型具有良好的检测精度和泛化能力,对于工业金刚石...

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Published in计算机集成制造系统 Vol. 29; no. 2; pp. 449 - 459
Main Authors 杨建新, 兰小平, 赵振, 杨一铭, 王波
Format Journal Article
LanguageChinese
Published 中国兵器工业信息中心,北京 100089 28.02.2023
Subjects
郊狼优化算法
反向学习
极限学习机
莱维飞行
工业金刚石
Online AccessGet full text
ISSN1006-5911
DOI10.13196/j.cims.2023.02.008

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Abstract TP183%TP391; 为了提高工业金刚石的检测效率、保障产品质量,提出一种基于改进郊狼算法与极限学习机的工业金刚石检测方法.将工业金刚石视频图像按照一定时间序列分解为一组较为平稳的、形态单一的二维图像数据;利用深度卷积网络Inception-V3对多视角二维图像数据建立预测模型;在此基础上,以预测结果为输入构建极限学习机模型,并利用反向学习和莱维飞行改进的郊狼算法优化极限学习机输入权值和阈值,提高工业金刚石模型的检测精度.最后将该模型的检测结果与基本极限学习机、差分进化算法、粒子群优化算法和基本郊狼算法优化的极限学习机模型检测结果比较表明,该模型具有良好的检测精度和泛化能力,对于工业金刚石的质量检测具有指导意义.
AbstractList TP183%TP391; 为了提高工业金刚石的检测效率、保障产品质量,提出一种基于改进郊狼算法与极限学习机的工业金刚石检测方法.将工业金刚石视频图像按照一定时间序列分解为一组较为平稳的、形态单一的二维图像数据;利用深度卷积网络Inception-V3对多视角二维图像数据建立预测模型;在此基础上,以预测结果为输入构建极限学习机模型,并利用反向学习和莱维飞行改进的郊狼算法优化极限学习机输入权值和阈值,提高工业金刚石模型的检测精度.最后将该模型的检测结果与基本极限学习机、差分进化算法、粒子群优化算法和基本郊狼算法优化的极限学习机模型检测结果比较表明,该模型具有良好的检测精度和泛化能力,对于工业金刚石的质量检测具有指导意义.
Author 兰小平
王波
赵振
杨一铭
杨建新
AuthorAffiliation 中国兵器工业信息中心,北京 100089
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Author_FL LAN Xiaoping
YANG Yiming
YANG Jianxin
ZHAO Zhen
WANG Bo
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反向学习
极限学习机
莱维飞行
工业金刚石
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