Data sorting method of lightweight wireless network based on deep learning of attention mechanism
Lightweight wireless network is usually used for resource-limited equipment,which makes the data transmission and processing capacity is limited,and the amount of data is huge,and the feature identification is difficult,resulting in low data sorting accuracy.Therefore,a lightweight wireless network data sorting method based on deep learning of attention mechanism is proposed.Calculate the characteristic value of the data,quantitatively preprocess the basic data,use the rough set algorithm of the field to calculate the redundant limit of data sorting,the data features are extracted in multiple stages,construct the data sorting pro-cess of attention mechanism deep learning network,and adopt the optimal screening method to realize the data sorting processing.The final test results show that for selected six data sorting test cycle,attention mechanism deep learning network data sorting method final data sorting average F-Score can reach more than 85%,in the attention mechanism of deep learning technology,the current design data sorting method more pertinence,higher efficiency,has the practical application value.
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