基于Python的数据处理及图形化分析平台的设计开发
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摘要
主观评估作为人机工程研发过程中重要的评估手段,为整车开发提供重要的依据。每个主观评估问卷涉及到几百个问题和几十名评测人员的数据处理,传统主观评估数据处理流程非常耗时,需要进行大量的统计计算。最终的结果如果没有可视化展示,对于开发人员很难直观的去发现问题从而有针对性的解决问题。为了快速的对主观评估数据进行处理和有针对性的解决问题,借助Python编程语言对评估数据进行分析和可视化展示,进而更加高效、直观地将数据的变化趋势和规律展现给研究者。
Subjective evaluation, as an important means of evaluation in the process of ergonomics research and development,provides an important basis for vehicle development. Each subjective assessment questionnaire involves hundreds of questions and dozens of Evaluator's data processing. The traditional subjective assessment data processing process is very time-consuming and needs a lot of statistical calculation. If the final result is not visualized, it is difficult for developers to find problems intuitively and solve them pertinently. In order to deal with the subjective evaluation data quickly and solve the problem pertinently, the Python programming language is used to analyze and visualize the evaluation data, and then more efficiently and intuitively show the changing trend and rules of the data to researchers.
Subjective evaluation, as an important means of evaluation in the process of ergonomics research and development,provides an important basis for vehicle development. Each subjective assessment questionnaire involves hundreds of questions and dozens of Evaluator's data processing. The traditional subjective assessment data processing process is very time-consuming and needs a lot of statistical calculation. If the final result is not visualized, it is difficult for developers to find problems intuitively and solve them pertinently. In order to deal with the subjective evaluation data quickly and solve the problem pertinently, the Python programming language is used to analyze and visualize the evaluation data, and then more efficiently and intuitively show the changing trend and rules of the data to researchers.
引文
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[2]An analysis of process industry production and inventory manage-ment systems[J].Daina R Dennis,Jack R.Meredith.Journal of Operation Management.2000.
[3]Advanced Data Clustering Methods of Mining Web Documents[J].Samuel Sambasivam,Nick Theodosopoulos.Issues in Informing Science and Information Techn.2006.
[4]数据可视化的基本原理与方法[M].科学出版社,陈为,2013.
[5]海洋数据管理与可视化平台设计[J].陈俊宁,胡乃军,刘青.中国科技信息.2015(02).
[6]基于脚本语言的海洋数据处理与可视化研究[D].纪伟.中国海洋大学2015.
[7]大数据可视分析综述[J].任磊,杜一,马帅,张小龙,戴国忠.软件学报.2014(09).
[8]汽车座椅静态舒适度的主客观评价方法研究[D].林凌云.吉林大学2012.
[9]基于体压分布的驾驶座椅舒适度研究[D].余江鸿.国防科学技术大学2008.
[10]汽车人机工程学[M].北京大学出版社,任金东,2010.