Abstract
Rough set theory is a powerful artificial intelligence based tool used for data analysis and mining inconsistent information systems. In the presence of inconsistent, incomplete, imprecise, or vague data, normal statistical based data analytic techniques lag behind. This paper discusses the code profiling for rough set theory on DSP and ARM processors. This work was undertaken to understand the performance of rough set theory on existing processors for mining/analyzing inconsistent nature of IoT application at fog/edge interface.
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