基于数据聚类的工程造价教育课程质量评价体系

IF 1.1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
K. Liang, Xiao-qing Cai, Lu Hui
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引用次数: 0

摘要

针对现有工程造价课程质量评价体系存在的评价效果差、系统响应时间长等问题,设计了一种基于数据聚类的工程造价教育课程质量评价体系。基础层数据采集模块用于采集工程造价教育课程的质量评价数据,并通过can通信模块将采集到的数据传输到上位机。上位机的处理器控制模块将数据传输给课程质量评估模块,处理器控制模块选择32位定点芯片TMS320F2812;课程质量评价模块接收到数据后,采用数据挖掘中的模糊物元接近聚类评价方法对工程造价教育课程质量进行评价。将评估结果传输到应用层供用户使用,并通过显示层的显示界面将评估结果显示给用户,完成系统设计。实验结果表明,所提出的系统能够完成工程造价教育课程的质量评价,系统评价的响应时间控制在400ms以内,提高了系统的响应效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quality evaluation system of engineering cost education curriculum based on data clustering
Aiming at the problems of poor evaluation effect and long system response time in the existing project cost course quality evaluation system, a project cost education course quality evaluation system based on data clustering is designed. The data acquisition module of infrastructure layer is used to collect the quality evaluation data of engineering cost education course, and the collected data is transmitted to the upper computer by can communication module. The processor control module in the upper computer transmits the data to the course quality evaluation module, and the processor control module selects 32-bit fixed-point chip TMS320F2812; After receiving the data, the course quality evaluation module uses the fuzzy matter-element proximity clustering evaluation method in data mining to evaluate the quality of engineering cost education courses. The evaluation results are transmitted to the application layer for users to use, and the evaluation results are displayed to users through the display interface of the display layer to complete the system design. The experimental results show that the proposed system can complete the quality evaluation of engineering cost education course, the response time of system evaluation is controlled within 400ms, and the response efficiency of the system is improved.
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来源期刊
EAI Endorsed Transactions on Scalable Information Systems
EAI Endorsed Transactions on Scalable Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.80
自引率
15.40%
发文量
49
审稿时长
10 weeks
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