[1]鄂旭,任骏原,毕嘉娜,等.基于粗糙变精度的食品安全决策树研究[J].计算机技术与发展,2014,24(01):242-245.
　E Xu[][],REN Jun-yuan[],BI Jia-na[],et al.Research on Decision Tree for Food Safety Based on Variable Precision Rough Sets[J].,2014,24(01):242-245.
点击复制

基于粗糙变精度的食品安全决策树研究()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年01期
页码:
242-245
栏目:
应用开发研究
出版日期:
2014-01-31

文章信息/Info

Title:
Research on Decision Tree for Food Safety Based on Variable Precision Rough Sets
文章编号:
1673-629X（2014）01-0242-04
作者:
鄂旭12; 任骏原1; 毕嘉娜1 ; 沈德海1
[1]渤海大学 信息科学与技术学院；[2]中国产业安全研究中心
Author(s):
E Xu[1][2]; REN Jun-yuan[1]; BI Jia-na[1]; SHEN De-hai[1]
关键词:
决策树; 粗糙集; 变精度; 置信度
Keywords:
decision tree; rough sets; variable precision; confidence
分类号:
TP311
文献标志码:
A
摘要:
食品安全决策是食品安全问题研究的一项重要内容。为了对食品安全状况进行分析，基于粗糙集变精度模型，提出了一种包含规则置信度的构造决策树新方法。这种新方法针对传统加权决策树生成算法进行了改进，新算法以加权平均变精度粗糙度作为属性选择标准构造决策树，用变精度近似精度来代替近似精度，可以在数据库中消除噪声冗余数据，并且能够忽略部分矛盾数据，保证决策树构建过程中能够兼容部分存在冲突的决策规则。该算法可以在生成决策树的过程中，简化其生成过程，提高其应用范围，并且有助于诠释其生成规则。验证结果表明该算法是有效可行的。
Abstract:
Food safety decision is an important content of food safety research. Based on variable precision rough sets model,a method of building decision tree with rules that have definite confidence is proposed for food safety analysis. It is an improvement for decision tree inducing approach presented in traditional methods. Present a new algorithm for constructing decision tree with variable precision weighted mean roughness as the criteria for selecting attribute. The new algorithm used variable precision approximate accuracy instead the approxi-mate accuracy. Noisy data of training sets are considered enough. Limited inconsistency is allowed to existed examples of the positive re-gions. So the decision tree is simplified and its extensive ability is improved and more comprehensible. Experiments show that the algo-rithm is feasible and effective.

相似文献/References:

[1]夏奇思 王汝传.基于属性约简的粗糙集海量数据分割算法研究[J].计算机技术与发展,2010,(04):5.
　XIA Qi-si,WANG Ru-chuan.Mass Data Partition for Rough Set on Attribute Reduction Algorithm[J].,2010,(01):5.
[2]杨静 张楠男 李建 刘延明 梁美红.决策树算法的研究与应用[J].计算机技术与发展,2010,(02):114.
　YANG Jing,ZHANG Nan-nan,LI Jian,et al.Research and Application of Decision Tree Algorithm[J].,2010,(01):114.
[3]张政超 关欣[] 何友 李应升 郭伟峰.粗糙集理论数据处理方法及其研究[J].计算机技术与发展,2010,(04):12.
　ZHANG Zheng-chao,GUAN Xin[],HE You,et al.Rough Sets Data Processing Method and Its Research[J].,2010,(01):12.
[4]杨乐婵 邓松 徐建辉.基于BP网络的洪灾风险评价算法[J].计算机技术与发展,2010,(04):232.
　YANG Le-chan,DENG Song,XU Jian-hui.Flood Risk Evaluation Algorithm on BP Net[J].,2010,(01):232.
[5]张学友 苗强 毛军军.基于粗糙度的一种分形维数计算方法[J].计算机技术与发展,2010,(05):136.
　ZHANG Xue-you,MIAO Qiang,MAO Jun-jun.A Calculation Method of Fractal Dimension Based on Roughness[J].,2010,(01):136.
[6]王伟 高亮 吴涛.粗糙集在经济分析中的应用[J].计算机技术与发展,2008,(04):158.
　WANG Wei,GAO Liang,WU Tao.Application of Rough Set in Economic Analysis[J].,2008,(01):158.
[7]耿波 仲红 徐杰 闫娜娜.用关联分析法对负荷预测结果进行二次处理[J].计算机技术与发展,2008,(04):171.
　GENG Bo,ZHONG Hong,XU Jie,et al.Using Correlation Analysis to Treat Load Forecasting Results[J].,2008,(01):171.
[8]胡琼凯 黄建华.基于协议分析和决策树的入侵检测研究[J].计算机技术与发展,2009,(06):179.
　HU Oiong-kai,HUANG Jian-hua.Intrusion Detection Based on Protocol Analysis and Decision Tree[J].,2009,(01):179.
[9]李学文 王小刚.优势信息系统的属性约简算法[J].计算机技术与发展,2009,(08):107.
　LI Xue-wen,WANG Xiao-gang.Algorithm on Attribute Reduction in Dominance Information System Based on Dominance Relation[J].,2009,(01):107.
[10]徐沈 吴涛[] 李国成.产业结构调整的量化分析[J].计算机技术与发展,2009,(08):178.
　XU Shen,WU Tao,LI Guo-cheng.Quantitative Analysis on Adjustment of Industrial Structure[J].,2009,(01):178.
[11]汪小燕 杨思春.一种基于分辨矩阵的新的属性约简算法[J].计算机技术与发展,2008,(02):77.
　WANG Xiao-yan,YANG Si-chun.A New Algorithm for AttributeReduction Based on Discernible Matrix[J].,2008,(01):77.
[12]孙林 徐久成 马媛媛.基于决策熵的决策树规则提取方法[J].计算机技术与发展,2007,(06):97.
　SUN Lin,XU Jiu-cheng,MA Yuan-yuan.Algorithm for Rules Extraction of Decision Tree Based on Decision Information Entropy[J].,2007,(01):97.
[13]丁春荣 李龙澍.一个基于粗集的决策树规则提取算法[J].计算机技术与发展,2007,(11):110.
　DING Chun-rong,LI Long-shu.A Rule Abstracting Algorithm of Decision Tree Based on Rough Set[J].,2007,(01):110.
[14]刘军.基于粒划分方法构建决策树的算法研究[J].计算机技术与发展,2012,(10):87.
　LIU Jun.Research on Algorithm of Constructing Decision Tree Based on Granulatio Division Method[J].,2012,(01):87.
[15]黄锦静,陈 岱,李梦天.基于粗糙集的决策树在医疗诊断中的应用[J].计算机技术与发展,2017,27(12):148.[doi:10.3969/ j. issn.1673-629X.2017.12.032]
　HUANG Jin-jing,CHEN Dai,LI Meng-tian.Application of Decision Tree Based on Rough Set in Medical Diagnosis[J].,2017,27(01):148.[doi:10.3969/ j. issn.1673-629X.2017.12.032]
[16]徐 曌,张 斌.基于约简矩阵和 C4．5 决策树的故障诊断方法[J].计算机技术与发展,2018,28(02):40.[doi:10．3969/j．issn．1673－629X．2018．02．010]
　XU Zhao,ZHANG Bin.A Fault Diagnosis Method Based on C4．5 Decision Tree and Ｒeduction Matrix[J].,2018,28(01):40.[doi:10．3969/j．issn．1673－629X．2018．02．010]
[17]徐 怡,余 浩,刘 刚,等.基于粗糙集的影响大学生心理健康的研究[J].计算机技术与发展,2020,30(05):121.[doi:10. 3969 / j. issn. 1673-629X. 2020. 05. 023]
　XU Yi,YU Hao,LIU Gang,et al.Research on College Students爷 Mental Health Based on Rough Set Theory[J].,2020,30(01):121.[doi:10. 3969 / j. issn. 1673-629X. 2020. 05. 023]

更新日期/Last Update: 1900-01-01