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The architecture of quality data mining in aerospace engineering
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Science & Technology Review | 2022, 40(6) : 101 - 109
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Science & Technology Review | 2022, 40(6): 101-109
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The architecture of quality data mining in aerospace engineering
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LIU Guocai
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    China Academy of Aerospace Standardization and Product Assurance, Beijing 100071, China
Published: 2022-03-28 doi: 10.3981/j.issn.1000-7857.2022.06.012
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Based on the DoDAF architecture framework theory, for the quality big data (data package) in aerospace engineering, a process model of the aerospace engineering quality data architecture is mined by the empirical method. The process model is consistent with the feedforward and feedback compound control system models, and it is shown that the space quality work follows the compound control mechanism of the feedforward and the feedback. Based on this mechanism, the typical quality data are selected from four dimensions and mined, and the important information about the "hot words", the data baseline and the quality problem predictions is obtained.
aerospace engineering  /  quality big data  /  architecture mining  /  quality SOS effectiveness
LIU Guocai. The architecture of quality data mining in aerospace engineering[J]. Science & Technology Review, 2022 , 40 (6) : 101 -109 . DOI: 10.3981/j.issn.1000-7857.2022.06.012
Year 2022 volume 40 Issue 6
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doi: 10.3981/j.issn.1000-7857.2022.06.012
  • Receive Date:2021-11-15
  • Online Date:2022-04-27
  • Published:2022-03-28
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  • Received:2021-11-15
  • Revised:2022-02-18
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表12种不同金属材料的力学参数

Family
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Number of
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种数
Number of
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占总种数比例
Percentage of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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