Optimizing Data Mining Efficiency in Professional Farmer Simulation Training System with Cloud-Edge Collaboration

Abstract

In the construction of agriculture modernization, the production need professional farmer. It is important that the professional farmer training in simulation production surrounding supported by agriculture internet of things. The application of the Internet of things generates massive data. It need optimize the smart mining method, which edge computing and cloud computing constitute an organic interaction system , with excellent functions in data intelligent mining. This paper based on the self-developed professional farmer training simulation system, aiming at the massive data in the system, a distributed deep learning algorithm based on the edge cloud collaboration be proposed, furthermore, optimized the algorithm by constructing the edge cloud collaboration network architecture of deep learning and the distributed parallel training be described, so as to solve the poor efficiency of intelligent mining of cloud alliance data in he simulation training system.