Power missing data filling method based on hybrid strategy
A technology with missing data and mixed strategies, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as increasing the amount of algorithm calculation, filling accuracy to be improved, modeling without data itself, etc., to improve accuracy , Simplify the difficulty of calculation and improve the effect of filling accuracy
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[0044] The accompanying drawings are for illustrative purposes only, and should not be construed as limitations on this patent; in order to better illustrate this embodiment, certain components in the accompanying drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product; for those skilled in the art It is understandable that some well-known structures and descriptions thereof may be omitted in the drawings. The positional relationship described in the drawings is for illustrative purposes only, and should not be construed as a limitation on this patent.
[0045] figure 1 It is an overall flow chart of the present invention, comprising the following steps:
[0046] S1. Using the improved k-Means clustering algorithm to cluster the data sets containing missing data;
[0047] S2. Improve and construct the RBF neural network according to the clustering results;
[0048] S3. Train the RBF neural network, and perform a filling test on the...
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