Research on Multi-source Data Fusion and Mining Based on Big Data

To solve the problem of massive multi-source data under the background of multi-sensor big data, a data fusion method which is easy to realize is used to fuse and mine the massive big data, and the difference between the fusion data and the real data is used as the stability judgment method. Compared with the measurement errors of single sensor and average estimation, it is proved that the heterogeneous sensor using weighted least square data fusion has higher measurement accuracy. The numerical examples are consistent with the theoretical derivation, which further verifies the effectiveness of the proposed method and improves the accuracy and mining effect of big data fusion.