中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Data mining-based engineering project grading technique

文献类型:会议论文

作者Chang CG(常春光); Song XY(宋晓宇); Gao B(高波); Kong, Fanwen
出版日期2008
会议名称7th World Congress on Intelligent Control and Automation
会议日期June 25-27, 2008
会议地点Chongqing, China
关键词Data mining Engineering project Grading Decision tree C4.5 algorithm
页码3542-3546
通讯作者常春光
中文摘要The purpose of this paper is to improve the quality of engineering project grading, the basic processes of data mining technique are introduced. Taking the engineering project grading as background, the implement cycles such as business understanding, data understanding, data preparation, modeling, evaluation and deployment are studied in detail. During modeling, the decision tree is adopted as analyzing modeling, and the conventional C4.5 algorithm is adapted. The adapted algorithm is applied to the engineering project grading, and its result is compared with that of conventional C4.5 algorithm. The comparing result demonstrates that for the complex system such as engineering project grading, it can improve in a certain extent on precision and obtained structure of decision tree, it can improve the quality of engineering project grading.
收录类别EI ; CPCI(ISTP)
产权排序1
会议主办者Chongqing Univ, Chongqing Inst Technol, Chongqing Univ Sci & Technol, Xihua Univ, SW Univ Sci & Technol, IEEE Robot & Automat Soc, IEEE Control Syst Soc, Beijing Chapter, Chinese Assoc Automat, Chinese Assoc Artificial Intell, Natl Nat Sci Fdn, Chongqing Municipal Sci & Technol Comm, Chongqing Municipal Assoc Sci & Technol, KC Wong Educ Fdn
会议录2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23
会议录出版者IEEE
会议录出版地NEW YORK
语种英语
ISBN号978-1-4244-2113-8
WOS记录号WOS:000259965702205
源URL[http://ir.sia.cn/handle/173321/19947]  
专题沈阳自动化研究所_工业信息学研究室_先进制造技术研究室
推荐引用方式
GB/T 7714
Chang CG,Song XY,Gao B,et al. Data mining-based engineering project grading technique[C]. 见:7th World Congress on Intelligent Control and Automation. Chongqing, China. June 25-27, 2008.

入库方式: OAI收割

来源:沈阳自动化研究所

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