摘要
运用知识库系统中数据分类知识的结构性特点,确定搜索最小约简解的下界;结合启发式约简算法获得的可行解为搜索上界,则可获得大大缩小的最小约简解搜索区间。在区间内优化搜索算法,快速地获得了数据集的最小约简解集。实例证明该运算途径简易、有效,为获取最小约简解的算法研究提供了参考。
By using the structural characteristic of data classification knowledge in knowledge base,we determine the lower bound of minimal reduction solution to be searched;by combining the feasible solution derived from heuristic reduction algorithm as the upper bound of search,the search region of minimal reduction solution,which has been greatly narrowed,is able to be got.By optimising the search algorithm within the region,we rapidly obtain the solution set of minimal reduction of dataset.It is proved by the examples that this algorithm is simple in operation approach and is effective as well,it provides the reference for the algorithms research in regard to obtaining minimal reduction solutions.
出处
《计算机应用与软件》
CSCD
北大核心
2014年第2期271-274,共4页
Computer Applications and Software
基金
国家自然科学基金项目(U0735003)
上海市教委科研创新项目(060Z021)
上海市应用技术学院项目(YJ2008-07)
关键词
最小约简
搜索区间
粗糙集
知识库系统
分类知识
Minimal reduction
Search region
Rough set
Knowledge base system
Classification knowledge