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作 者:张适韫 申黎明 ZHANG Shiyun;SHEN Liming(College of Furnishings and Industrial Design,Nanjing Forestry University,Nanjing 210037,China)
机构地区:[1]南京林业大学家居与工业设计学院,南京210037
出 处:《包装工程》2024年第20期205-213,共9页Packaging Engineering
摘 要:目的了解国内外办公椅舒适性研究现状,明确国内办公椅舒适性研究的不足与空白部分,以明确未来的重点研究方向,预测国内外研究趋势。方法以中国知网中的中文数据和Web of science核心合集中的英文数据作为数据来源,利用Cite Space和VOSviewer软件对国内外文献数据中的关键词进行可视化分析,基于分析结果从研究热点和研究历程两个方面梳理国内外研究现状,并横纵向对比国内外研究状况以找到国内研究的不足之处。结论办公椅舒适性研究是办公椅研究领域的热点;国内办公椅舒适性研究起步晚于国外约20年,且每个研究阶段落后国外约10年。国外该领域研究时间长,研究范围广,国内在热舒适性、能量节约、身体不适等研究方面有所欠缺,未来应重点研究;未来办公椅舒适性研究极可能向结合人工智能的方向发展,基于神经网络、机器学习、深度学习的研究是未来发展的热点。The work aims to understand the research status of office chair comfort at home and abroad and clarify the shortcomings and gaps of domestic office chair comfort research,so as to define the key research directions in the future and predict the research trend at home and abroad.With the Chinese data in CNKI and the English data in the core collec-tion of Web of science as the data source,Cite Space and VOSviewer software were used to visually analyze the keywords in the domestic and foreign literature data.Based on the analysis results,the research status at home and abroad was sorted out from two aspects:research hotspots and research process,and the research status at home and abroad was compared horizontally and vertically to find the shortcomings of domestic research.In conclusion,the research on the comfort of office chairs is a hot spot in the field of office chair research.The research on the comfort of domestic office chairs started about 20 years later than abroad,and each research stage lagged behind foreign countries by about ten years.Foreign research in this field has a long time and a wide range of research,and there are deficiencies in research on ther-mal comfort,energy saving,physical discomfort and other aspects in China.It should be focused on research in the future.The future office chair comfort research is likely to develop in the direction of combining artificial intelligence,and the research based on neural networks,machine learning,and deep learning is a hot spot for future development.
分 类 号:TB472[一般工业技术—工业设计]
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