Multi-modal prediction method of power grid big data based on tensor chain
CHEN Bin
XU Huan
ZOU Wenjing
Abstract：In order to optimize the accuracy and computing time of big data prediction system,a multi-modal prediction method based on tensor theory for power grid was proposed.By employing the tensor and Markov theories,a multi-variate and multi-order Markov model with strong adaptability and a Markov transfer method without hypothesis were designed.On this basis,the short-term and long-term prediction algorithms based on tensor chain theory were constructed,thus the multi-modal prediction method of big data with low computational complexity was proposed.The simulation results show that the multi-modal prediction method based on tensor chain has higher prediction accuracy and lower computing time in comparison with the classical Markov prediction method.
Keywords：big datatensor chainmain eigenvaluemulti-modal predictionparallel computingMarkov modelcomplexity analysisprediction accuracy
Publication Date：2024-01-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 13-18 )