Multi-dimensional visualization multi-source heterogeneous data multi-layer drnn deep fusion method
A technology of multi-source heterogeneous data and fusion method, which is applied in the field of deep fusion of multi-source heterogeneous data and multi-layer DRNN, can solve the problems that the direct display of heterogeneous data cannot be guaranteed
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[0040] like figure 1 , figure 2 and image 3 As shown, the multi-dimensional visualized multi-source heterogeneous data multi-layer DRNN deep fusion method is characterized in that: the method steps include:
[0041] Step 1: Establish DRNN neural network;
[0042] For multi-source heterogeneous data, establish a recursive self-learning network based on deep neural network; establish a deep learning model, and form a recursive network at each layer. The recursive network uses deep self-learning to generate a DRNN network; build a DRNN network close to the underlying data There is no link between the nodes in the layer, and fuzzy fusion judgment is used in the farthest part, and the corresponding generation model is obtained by increasing the number of hidden layers through forward self-encoding.
[0043] The specific method of establishing a recursive self-learning network based on deep warp network is:
[0044] Using a layered architecture, each layer adaptively establish...
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