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作 者:王映龙[1] 华佳佳 钱文彬[2] 杨珺[2] WANG Yinglong;HUA Jiajia;QIAN Wenbin;YANG Jun(School of Computer and Information Engineering, Jiangxi Agricultural University, Nanchang 330045, China;School of Software, Jiangxi Agricultural University, Nanchang 330045, China)
机构地区:[1]江西农业大学计算机与信息工程学院,南昌330045 [2]江西农业大学软件学院,南昌330045
出 处:《计算机工程与应用》2017年第17期60-64,共5页Computer Engineering and Applications
基 金:国家自然科学基金(No.61502213;No.61462038);江西省自然科学基金(No.20151BAB217009;No.20132BAB201045);江西省教育厅科学技术项目(No.GJJ150399)
摘 要:在现实应用中许多数据往往是动态变化的,静态的属性约简算法处理此类数据需消耗大量的计算时间和存储空间。针对集值决策信息系统中数据的动态变化情况,通过引入条件信息量和属性重要性概念,提出了一种启发式的动态属性约简算法,当新的属性集增加到决策信息系统时,算法能够利用原系统的属性约简结果,快速更新属性集增加后的属性约简,并对更新后的属性约简中可能存在的冗余属性进行反向剔除,保持了知识获取的简洁,提高了算法的计算效率。最后,通过实例验证进一步分析了算法的有效性和可行性。Many data sets often vary dynamically in practical applications.Static attribute reduction algorithms consume alot of time and space to solve these dynamical data sets.Since the data in set-valued decision information system are usually changed,a heuristic dynamic updating algorithm of attribute reduction is designed by introducing the concepts of conditional information quantity and significance of attribute.When new condition attributes are added to the set-valued decision information system,the proposed algorithm makes use of the attribute reduction results of the old system,updates the attribute reduction results quickly with the variation of attribute set,and deletes some redundant attributes in the new result of attribute reduction in reverse order,which keeps the knowledge concise and improves the computational efficiency.Finally,the effectiveness and feasibility of the proposed algorithm are validated by the examples.
分 类 号:TP311[自动化与计算机技术—计算机软件与理论]
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