基于酶数值P系统的大数据场分析方法

Handling Big Data Field with Enzymatic Numerical P System

为了解决大数据环境下快速求解数据场势值的计算效率问题,基于膜计算领域的酶数值P系统(ENPS),提出一种数据场分析方法。该方法先引入转移P系统对ENPS加以改进,以提高后者的流程可控性,再基于改进的系统给出计算大数据场势值的ENPS的具体实现。P系统的极大并行性导致大数据场势值求解在3步内完成,每个步骤的计算时间为常数,且与数据规模无关。在真实人脸图像数据场上的实验结果验证了此方法的高效性。

：An approach to analyze data field was proposed to compute the data field potential in the setting of big data based on the en- zymatic numerical P system（ENPS） which is a novel membrane computing device. At first, this approach employed the transition P system to improve the ENPS so as to enhance the controllability of processes. Then, the improved ENPS was taken into account to de- sign a P system for calculating the potential of big data field. The maximum parallelism of the P system resulted in the accomplishment of calculation on the potential of big data field only in three steps. The running time within each step was constant and independent to the data scale. Experimental results on real data field from face images verified the effectiveness of the proposed method.