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C4.5算法在工程质量决策支持系统中的应用研究 被引量:1

Applied Research of C4.5 Algorithm in Engineering Quality Decision Support System
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摘要 由于传统的水利工程质量监督管理系统只是起到监管的作用,难以发现并预测工程质量上潜在的问题。针对这一现象,提出了采用决策树C4.5算法对工程质量进行决策支持的解决方案。首先概述了决策树算法和C4.5算法,然后详细阐述了决策支持系统中数据预处理、利用C4.5算法进行数据建模的过程,最后根据建立好的决策树模型开发决策支持系统。实验结果表明:用C4.5算法建立的决策树模型准确率较高,开发的决策支持系统能很好地应用到实际工程质量监督的过程中并达到了预期目的,能较好地对未来工程质量进行预测,给监督部门提供决策支持。 As traditional hydraulic engineering quality supervision and management system just playing the role of regulation,it is difficult to detect and predict potential problems on the quality of the project. Aiming at this phenomenon,a solution about using the C4. 5 algorithm to make decision on project quality was proposed. First provided an overview of the algorithm and C4. 5 decision tree algorithm and then elaborated data preprocessing and the process about data modeling used with C4. 5 algorithm in decision support system. Finally developed the decision support system according to the decision tree model. The experimental results show that the decision tree model established by C4. 5 algorithm has high accuracy. The developed decision support system can be well applied to practical engineering quality supervision process and achieves the desired results. It can be better for the future project quality prediction,providing decision support to the supervision department.
作者 侯立铎 叶洁
出处 《计算机技术与发展》 2016年第2期132-135,共4页 Computer Technology and Development
基金 贵州省科技计划项目(黔科合GY字(2011)3050)
关键词 C4.5算法 信息熵 工程质量 WEKA C4.5 algorithm entropy project quality Weka
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参考文献12

  • 1罗可,林睦纲,郗东妹.数据挖掘中分类算法综述[J].计算机工程,2005,31(1):3-5. 被引量:63
  • 2陈文伟,邓苏,张维明.数据开采与知识发现综述[M].北京:机械工业出版社,2003.
  • 3Tsang S, Kao B, Yip K Y, et al. Decision trees for uncertain data[ C ]//Proc of IEEE international conference on data en- gineering. Shanghai, IEEE ,2009:441-444.
  • 4桂现才,彭宏,王小华.C4.5算法在保险客户流失分析中的应用[J].计算机工程与应用,2005,41(17):197-199. 被引量:33
  • 5刘兵.Web数据挖掘[M].北京:清华大学出版社,2009.
  • 6Chen Jin, Luo Delin, Mu Fenxiang. An improved ID3 decision tree algorithm [ C]//Proc of 4th international conference on IEEE computer science and education. Chengdu : IEEE ,2009 : 127-130.
  • 7Barnum H ,Barrett J ,Clark L O,et al. Entropy and information causality in general probabilistic theories [ J ]. New Journal of Physics,2010,12 ( 3 ) : 1-32.
  • 8Kantardzic M. Data mining: concepts, models, and algorithms [ M ]. New York :John Wiley and 1EEE Press ,2003.
  • 9Zhou Chi, Xiao Weimin, Tirpak T M, et al. Evolving accurate and compact classification rules with gene expression program- ming [ J ]. IEEE Transactions on Evolutionary Computation, 2003,7(6) :519-53.1.
  • 10HanJiawei,MichelineKambe.数据挖掘概念与技术[M].北京:机械工业出版社,2012:13.

二级参考文献31

  • 1李青,焦李成,周伟达.基于向量投影的支撑向量预选取[J].计算机学报,2005,28(2):145-152. 被引量:37
  • 2姚再勇,郑启龙,许胤龙,姚震,张红涛,胡晨光.基于Eclipse的并行开发环境EMPI[J].计算机应用与软件,2005,22(10):5-7. 被引量:3
  • 3沈云斐,沈国强,蒋丽华,覃征.基于时效性的Web页面个性化推荐模型的研究[J].计算机工程,2006,32(13):80-81. 被引量:6
  • 4林金晓,陈伟男,周学功,彭澄廉,吴荣泉.基于Eclipse平台的边界扫描测试软件的开发[J].计算机工程,2007,33(12):280-282. 被引量:5
  • 5Dell Zhang.A novel Web usage mining approach for search engines[J].Computer Networks,2002,39:303-310.
  • 6Abraham.Web usage mining using artificial ant colony clustering and genetic programming [C]. Congress on Evolutionary Computation.Australia:IEEE Press,2003.
  • 7Ali A Ghorbani,Xu Xiaowen.A fuzzy markov model approach for predicting user navigation[C].IEEE/WIC/ACM International Conference on Web Intelligence,2007:307-311.
  • 8Supfiya Kumar De,Radha Krishna EClustering web transactions using rough apptoximation[J].Fuzzy Sets Aand Systems,2004, 148:131-138.
  • 9UCI machine learning repository[EB/OL].http://mlearn.ics.uci. edu/MLRepository.html.
  • 10JiaweiHart 范明 孟小峰译.MichelineKamber,数据挖掘概念与技术[M].北京:机械工业出版社,2001..

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