Big data analysis method adopting grey wolf optimization algorithm
An optimization algorithm and analysis method technology, applied in the field of big data analysis, can solve the problems of large data volume, high computational complexity, long processing time for a single machine, etc., to achieve the effect of improving operating efficiency and high search performance
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[0018] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.
[0019] Gray Wolf Optimizer (GWO) was proposed by Australian scholar Mirjalili in 2014. By simulating the social class of gray wolves, the predation tasks such as siege, hunt and attack are assigned to different levels of gray wolves to complete the predation behavior. So as to realize the process of global optimization. At present, GWO, as a new heuristic optimization method, has been successfully applied to optimization problems such as power systems.
[0020] With the explosive growth of data volume, it has become a trend to process these huge data volumes...
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