Collaborative decision-making of multi-source heterogeneous sensing data for smart power IoT

Abstract

The current multi-source heterogeneous sensing data collaborative decision-making method based on machine learning achieves the fusion of sensing data through data sensing technology, which leads to the poor comprehensive collaborative performance of the model due to the low data processing accuracy. In this regard, multi-source heterogeneous sensing data collaborative decision-making for smart power IoT is proposed. A data reliability analysis framework is established to analyze the unstable factors affecting the fluctuation of sensing data, and the data is slimmed down. And the feature vectors of the sensed data are extracted to establish the data collaborative decision-making model. In the experiments, the comprehensive collaborative performance of the proposed method is verified. The analysis of the experimental results shows that the collaborative decision model of sensing data constructed by the proposed method has a high level of comprehensive evaluation and its collaborative decision performance is high.