| Summary: | In order to improve the efficiency and accuracy of network large data transmission and reduce the network data transmission load, a network large data fusion algorithm based on multilayer probabilistic network model and joint decision making is studied. Firstly, based on the data acquisition and caching of complex heterogeneous multi-layer networks, a multi-level probabilistic joint decision model is designed, which takes real-time sensing data and its accurate processing as the optimization objective. Then, through the main layer stratification and the signal strength of multidimensional network big data description, combined with the three step decomposition and three fusion, driven by transform denoising, the network data collaboration data fusion algorithm is proposed. Finally, the experimental and simulation results show that the proposed algorithm has obvious advantages in terms of data fusion accuracy and efficiency compared with experimental statistics.
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