基于密集型数据复写的复杂项目增长趋势检测

Complex Projects Increase Detection Algorithm Based on Intensive Data Replication

在密集型复写的复杂项目环境中,数据具有数量丰富、分布、异构、高速变化、结构或半结构的特点,传统的数据处理方式是把数据全部传输到相应的数据处理节点,无法解决数据密集型计算环境下数据可用性的问题,导致以数据为中心的计算中数据存储与处理、分析与挖掘、增长趋势检测等研究结果相应地发生改变。提出了一种CTDA检测算法,分别对CQAR算法和COPIT算法进行改进,将两算法合并,使其有效解决数据密集型计算环境下的数据分析挖掘及增长趋势检测。算法性能测试结果表明,CTDA检测算法,提高了算法的精准度,可对基于密集型数据复写的复杂项目增长趋势作出合理的检测。

In the complex project environment, to intensive data has a number of rich, distributed, heterogeneous, high speed changes, the characteristics of the structure or structure, traditional way of data processing is transmitting all the data to the corresponding data processing node, unable to solve the data intensive computing environment data usability prob-lems, causing a data-centric calculation data storage and processing, analysis and mining, the growth trend of test results such as the corresponding change. A CTDA detection algorithm is proposed in this paper, to improve the CQAR algorithm and COPIT algorithm respectively, merge the two algorithm, make it effective to solve data intensive computing environ-ment analysis of data mining and the growing trend detection. Algorithm performance test results show that CTDA detection algorithm, improve the precision of the algorithm, based on intensive data to autotype reasonable complex project growth trend of detection.