AUTONOMOUS MINING METHOD OF INDUSTRIAL BIG DATA BASED ON MODEL SETS

Fecha de publicación: 21/09/2023
Fuente: Wipo "BigData"
Disclosed is an autonomous mining method of industrial big data based on model sets, which comprises the following steps: S1, building model sets and a mining engine based on domain knowledge and structural characteristics of multi-source heterogeneous data; S2, carrying out data sampling on the multi-source heterogeneous data, and counting the fault-tolerant estimation of random error variance; S3, mining data sets by using the mining engine, and determining the optimal fault-tolerant model of each sampled data sequence and the optimal fault-tolerant estimation of model parameters; S4, performing goodness-of-fit statistics calculation and VV&A test by using the optimal fault-tolerant model; S5, acquiring data model representation and connotation knowledge based on model clustering. The method can realize the automation of the mining process of big data, the integration of associated knowledge, the expansion of model sets, the integration of mining and modeling and the optimization of mining results.