摘要
多输入输出(MIMO)级联数据库广泛应用在大型电子设备故障诊断数据库架构中。对MIMO级联数据库频繁访问过程中,进行特征分区有利于提高数据库访问性能。提出一种基于属性集合幂集的区间概念格的非线性MIMO级联数据库频繁访问特征分区算法,进行MIMO级联数据库的非线性特征分析及区间概念格构造,对数据库子系统的状态矢量进行临界状态数学建模,构建数据库的特征分区目标函数,改进MIMO级联数据库频繁访问特征分区性能。仿真实验表明,该算法能准确实现对非线性MIMO级联数据库频繁访问特征的提取和分区处理,有效提高了对MIMO级联数据库的内部访问特征的分析能力,有利于提高数据库访问性能,大幅提高数据检测性能,为构建专家系统奠定基础。
Multi input multi output（MIMO） cascade database widely is used in fault diagnosis database framework for large scale electronic equipment. Frequent access to the database of MIMO cascade process, feature partition is conducive to improve the performance of database access. A frequent access feature partition algorithm of nonlinear cascaded MIMO database interval concept lattice attribute set power set is proposed based on the nonlinear characteristic analysis and interval concept lattice structure are cascaded MIMO database, the database subsystem of the state vector of the critical state of mathematical modeling, feature partition object function for constructing the database, it can improve the MIMO database access frequently cascade the performance characteristics of partition. The simulation experiment shows that this algorithm can accurately realize the extraction and partition handling of nonlinear MIMO cascade database frequent access characteristics, it can effectively improve the ability of analysis of the internal access features of the MIMO cascade database, it can improve the performance of database access, and improve the data detection performance, it provides lay the foundation for the construction of expert system.
出处
《科技通报》
北大核心
2015年第4期43-45,共3页
Bulletin of Science and Technology
