Research on Big Data Analytics by Using High-Level Fuzzy Petri Nets

Abstract

The aim of this study is to apply the theory of high-level fuzzy Petri nets (HLFPN) to big data analytics platform. The platform features the following advantages: 1) it enables to describe analytical contents through natural language approaches; 2) it can be used to verify analytical processes through modular approaches; 3) it enables to promote fuzzy theory and solving problems through nonlinear equations; 4) it can be employed to generate Map/Reduce programs automatically through the system; 5) it can be used for parallelization, thereby shortening analysis time; and 6) it enables to inquire results through an interface. Finally, we describe the experiments conducted to verify the functions of the platform.