Wireless sensor network data compression sampling technology based on unbalanced data collaborative filtering

In order to improve the data acquisition capability of wireless sensor networks, a data compression sampling technology based on unbalanced data collaborative filtering is proposed. Establishing a data compression sampling state feature analysis model, designing a linear kernel function, a probability density feature kernel function and a Gaussian kernel function for wireless sensor network communication transmission data compression sampling, realizing wireless sensor network data compression and feature separation by an unbalanced data collaborative filtering method, constructing a boundary solution vector function for data compression sampling by adopting a support vector machine model, and realizing classification processing after data feature compression by adopting a fuzzy c-means clustering analysis method. Combined with threshold judgment method, the filtering analysis and subspace noise reduction of wireless sensor network data compression are realized, and the unbalanced data collaborative filtering detection model is constructed. According to the data feature detection results, the wireless sensor network data compression sampling is realized. The simulation results show that the feature clustering of wireless sensor network data compression sampling is better and the data detection accuracy is higher.