基于蚁群优化的数字化审计系统数据快速查询方法

Fast Data Query Method of Digital Audit System Based on Ant Colony Optimization

由于数字化审计系统中的数据量较大,降低了数据查询效率和查准率,为此提出基于蚁群优化的数字化审计系统数据快速查询方法。采用分布式链路节点跟随识别的方法采集数字化审计系统数据,并对采集的数据进行非线性样本重组,结合模板匹配和线性规划设计的方法对数字化审计系统数据降维处理,提取数据特征;在此基础上,根据蚁群个体的差异性对数字化审计系统数据查询的异常特征进行判断,获取数据的可靠性文本结构特征量,对文本结构特征量进行加窗处理,根据处理结果,利用蚁群寻优方法构建查询控制函数,获取全局最优解,实现对数字化审计系统数据的快速查询。仿真结果表明,采用该方法进行数字化审计系统数据查询的实时性较好,查准率较高,具有较好的可靠性检索能力。

Due to the large amount of data in the digital audit system,the efficiency and accuracy of data query are reduced.For this reason,a fast query method of digital audit system data based on ant colony optimization is proposed.It adopts distributed link node follow-up identification method to collect digital audit system data,and performs nonlinear sample reorganization of the collected data,combines template matching and linear programming design methods to reduce the dimensionality of digital audit system data,and extracts data characteristics.On this basis,according to the individual differences of the ant colony,the abnormal characteristics of the data query of the digital audit system are judged,the reliability of the text structure feature of the data is obtained,and the text structure feature is windowed.According to the processing result,the ant group optimization method is used to construct the query control function.The method can obtain the global optimal solution,and realize the rapid query of the digital audit system data.The simulation results show that the method has better real-time performance,higher accuracy,and better reliability retrieval ability for data query of digital audit system.