人工智能与激光技术#交叉研究态势分析  

Analysis of Cross Research Trends between Artificial Intelligence and Laser Technology

作　　者：刘德娟 沈力[1] Liu Dejuan;Shen Li(Information Management Center,Shanghai Institute of Optics and FineMechanics,Chinese Academy of Sciences,Shanghai201800)

机构地区：[1]中国科学院上海光学精密机械研究所信息管理中心,上海201800

出　　处：《应用激光》2024年第12期89-101,共13页Applied Laser

基　　金：2020年“中国科学院文献情报领域引进优秀人才计划”择优支持项目(科发规函字[2020]17号)。

摘　　要：以WebofScience数据库中1989~2022年人工智能与激光技术交叉研究领域相关学术论文3621篇为研究对象,运用统计学和文献计量学软件DDA、CiteSpace对其文献分布特征、热点主题词、主题词聚类、新兴趋势以及高被引论文进行分析。结果表明,中国发文量全球第一,总被引次数全球第二,但是从篇均被引频次上来看,明显偏低,低于全球篇均被引频次,整体发文质量有待进一步提高。从热点主题词来看,机器学习、深度学习、卷积神经网络、激光雷达、人工神经网络、增材制造、分类、点云、激光诱导击穿光谱和特征提取等主题词成为该领域热点关键词。包括生命健康、激光雷达、增材制造和元素分析等四个主要方面的应用。其中,深度学习、增材制造、三维显示、点云、激光粉末床熔融和卷积神经网络等关键词成为该领域新兴趋势的代表。Based on the WOS database,this paper collects a total of 3621 relevant literatures in the field of artificial intelligence and laser technology from 1989 to 2022.The visualization software DDA and CiteSpace were used to conduct bibliometric analysis of the literatures distribution characteristics,hot topics,keywords clustering,emerging trends and highly cited papers.The results show that the number of published papers in China ranks first in the world,and the total number of citations ranks second in the world.However,the frequency of cited articles is obviously low,lower than that of the global average mean.The overall quality of papers need to be further improved.Machine learning,deep learning,convolutional neural network,laser radar,artificial neural networks,additive manufacturing,classification,point cloud,laser-induced breakdown spectroscopy and feature extraction have become the hot keywords in this field.Including life health,laser radar,additive manufacturing and elemental analysis of four major applications.Among them,keywords such as deep learning,additive manufacturing,3D display,point cloud,laser powder bed fusion and convolutional neural networks have become research trends in recent years.

关 键 词：人工智能 激光技术 可视化分析 文献计量 研究热点 

分 类 号：G35[文化科学—情报学]